WorldWideScience

Sample records for reservoir release forecast

  1. Energy optimization through probabilistic annual forecast water release technique for major storage hydroelectric reservoir

    International Nuclear Information System (INIS)

    Abdul Bahari Othman; Mohd Zamri Yusoff

    2006-01-01

    One of the important decisions to be made by the management of hydroelectric power plant associated with major storage reservoir is to determine the best turbine water release decision for the next financial year. The water release decision enables firm energy generated estimation for the coming financial year to be done. This task is usually a simple and straightforward task provided that the amount of turbine water release is known. The more challenging task is to determine the best water release decision that is able to resolve the two conflicting operational objectives which are minimizing the drop of turbine gross head and maximizing upper reserve margin of the reservoir. Most techniques from literature emphasize on utilizing the statistical simulations approach. Markovians models, for example, are a class of statistical model that utilizes the past and the present system states as a basis for predicting the future [1]. This paper illustrates that rigorous solution criterion can be mathematically proven to resolve those two conflicting operational objectives. Thus, best water release decision that maximizes potential energy for the prevailing natural inflow is met. It is shown that the annual water release decision shall be made in such a manner that annual return inflow that has return frequency smaller than critical return frequency (f c ) should not be considered. This criterion enables target turbine gross head to be set to the well-defined elevation. In the other words, upper storage margin of the reservoir shall be made available to capture magnitude of future inflow that has return frequency greater than or equal to f c. A case study is shown to demonstrate practical application of the derived mathematical formulas

  2. Probing magma reservoirs to improve volcano forecasts

    Science.gov (United States)

    Lowenstern, Jacob B.; Sisson, Thomas W.; Hurwitz, Shaul

    2017-01-01

    When it comes to forecasting eruptions, volcano observatories rely mostly on real-time signals from earthquakes, ground deformation, and gas discharge, combined with probabilistic assessments based on past behavior [Sparks and Cashman, 2017]. There is comparatively less reliance on geophysical and petrological understanding of subsurface magma reservoirs.

  3. Inflow forecasting using Artificial Neural Networks for reservoir operation

    Directory of Open Access Journals (Sweden)

    C. Chiamsathit

    2016-05-01

    Full Text Available In this study, multi-layer perceptron (MLP artificial neural networks have been applied to forecast one-month-ahead inflow for the Ubonratana reservoir, Thailand. To assess how well the forecast inflows have performed in the operation of the reservoir, simulations were carried out guided by the systems rule curves. As basis of comparison, four inflow situations were considered: (1 inflow known and assumed to be the historic (Type A; (2 inflow known and assumed to be the forecast (Type F; (3 inflow known and assumed to be the historic mean for month (Type M; and (4 inflow is unknown with release decision only conditioned on the starting reservoir storage (Type N. Reservoir performance was summarised in terms of reliability, resilience, vulnerability and sustainability. It was found that Type F inflow situation produced the best performance while Type N was the worst performing. This clearly demonstrates the importance of good inflow information for effective reservoir operation.

  4. Multi-data reservoir history matching for enhanced reservoir forecasting and uncertainty quantification

    KAUST Repository

    Katterbauer, Klemens; Arango, Santiago; Sun, Shuyu; Hoteit, Ibrahim

    2015-01-01

    Reservoir simulations and history matching are critical for fine-tuning reservoir production strategies, improving understanding of the subsurface formation, and forecasting remaining reserves. Production data have long been incorporated

  5. Uncertainty Assessment: Reservoir Inflow Forecasting with Ensemble Precipitation Forecasts and HEC-HMS

    Directory of Open Access Journals (Sweden)

    Sheng-Chi Yang

    2014-01-01

    Full Text Available During an extreme event, having accurate inflow forecasting with enough lead time helps reservoir operators decrease the impact of floods downstream. Furthermore, being able to efficiently operate reservoirs could help maximize flood protection while saving water for drier times of the year. This study combines ensemble quantitative precipitation forecasts and a hydrological model to provide a 3-day reservoir inflow in the Shihmen Reservoir, Taiwan. A total of six historical typhoons were used for model calibration, validation, and application. An understanding of cascaded uncertainties from the numerical weather model through the hydrological model is necessary for a better use for forecasting. This study thus conducted an assessment of forecast uncertainty on magnitude and timing of peak and cumulative inflows. It found that using the ensemble-mean had less uncertainty than randomly selecting individual member. The inflow forecasts with shorter length of cumulative time had a higher uncertainty. The results showed that using the ensemble precipitation forecasts with the hydrological model would have the advantage of extra lead time and serve as a valuable reference for operating reservoirs.

  6. Monthly reservoir inflow forecasting using a new hybrid SARIMA ...

    Indian Academy of Sciences (India)

    Seasonal autoregressive integrated moving average (SARIMA) models have been frequently ... studied the perfor- mance of stochastic models against ANN models in ..... the model parameters and Se is the standard error. 2.1.3 Nonlinear term ...... ison of regression, ARIMA and ANN models for reservoir inflow forecasting ...

  7. Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

    Science.gov (United States)

    Zhao, T.; Cai, X.; Yang, D.

    2010-12-01

    Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover

  8. Surrogate reservoir models for CSI well probabilistic production forecast

    Directory of Open Access Journals (Sweden)

    Saúl Buitrago

    2017-09-01

    Full Text Available The aim of this work is to present the construction and use of Surrogate Reservoir Models capable of accurately predicting cumulative oil production for every well stimulated with cyclic steam injection at any given time in a heavy oil reservoir in Mexico considering uncertain variables. The central composite experimental design technique was selected to capture the maximum amount of information from the model response with a minimum number of reservoir models simulations. Four input uncertain variables (the dead oil viscosity with temperature, the reservoir pressure, the reservoir permeability and oil sand thickness hydraulically connected to the well were selected as the ones with more impact on the initial hot oil production rate according to an analytical production prediction model. Twenty five runs were designed and performed with the STARS simulator for each well type on the reservoir model. The results show that the use of Surrogate Reservoir Models is a fast viable alternative to perform probabilistic production forecasting of the reservoir.

  9. Exploring the interactions between forecast accuracy, risk perception and perceived forecast reliability in reservoir operator's decision to use forecast

    Science.gov (United States)

    Shafiee-Jood, M.; Cai, X.

    2017-12-01

    Advances in streamflow forecasts at different time scales offer a promise for proactive flood management and improved risk management. Despite the huge potential, previous studies have found that water resources managers are often not willing to incorporate streamflow forecasts information in decisions making, particularly in risky situations. While low accuracy of forecasts information is often cited as the main reason, some studies have found that implementation of streamflow forecasts sometimes is impeded by institutional obstacles and behavioral factors (e.g., risk perception). In fact, a seminal study by O'Connor et al. (2005) found that risk perception is the strongest determinant of forecast use while managers' perception about forecast reliability is not significant. In this study, we aim to address this issue again. However, instead of using survey data and regression analysis, we develop a theoretical framework to assess the user-perceived value of streamflow forecasts. The framework includes a novel behavioral component which incorporates both risk perception and perceived forecast reliability. The framework is then used in a hypothetical problem where reservoir operator should react to probabilistic flood forecasts with different reliabilities. The framework will allow us to explore the interactions among risk perception and perceived forecast reliability, and among the behavioral components and information accuracy. The findings will provide insights to improve the usability of flood forecasts information through better communication and education.

  10. Financial Risk Reduction and Management of Water Reservoirs Using Forecasts: A Case for Pernambuco, Brazil

    Science.gov (United States)

    Kumar, I.; Josset, L.; e Silva, E. C.; Possas, J. M. C.; Asfora, M. C.; Lall, U.

    2017-12-01

    The financial health and sustainability, ensuring adequate supply, and adapting to climate are fundamental challenges faced by water managers. These challenges are worsened in semi-arid regions with socio-economic pressures, seasonal supply of water, and projected increase in intensity and frequency of droughts. Over time, probabilistic rainfall forecasts are improving and for water managers, it could be key in addressing the above challenges. Using forecasts can also help make informed decisions about future infrastructure. The study proposes a model to minimize cost of water supply (including cost of deficit) given ensemble forecasts. The model can be applied to seasonal to annual ensemble forecasts, to determine the least cost solution. The objective of the model is to evaluate the resiliency and cost associated to supplying water. A case study is conducted in one of the largest reservoirs (Jucazinho) in Pernambuco state, Brazil, and four other reservoirs, which provide water to nineteen municipalities in the Jucazinho system. The state has been in drought since 2011, and the Jucazinho reservoir, has been empty since January 2017. The importance of climate adaptation along with risk management and financial sustainability are important to the state as it is extremely vulnerable to droughts, and has seasonal streamflow. The objectives of the case study are first, to check if streamflow forecasts help reduce future supply costs by comparing k-nearest neighbor ensemble forecasts with a fixed release policy. Second, to determine the value of future infrastructure, a new source of supply from Rio São Francisco, considered to mitigate drought conditions. The study concludes that using forecasts improve the supply and financial sustainability of water, by reducing cost of failure. It also concludes that additional infrastructure can help reduce the risks of failure significantly, but does not guarantee supply during prolonged droughts like the one experienced

  11. Daily reservoir inflow forecasting combining QPF into ANNs model

    Science.gov (United States)

    Zhang, Jun; Cheng, Chun-Tian; Liao, Sheng-Li; Wu, Xin-Yu; Shen, Jian-Jian

    2009-01-01

    Daily reservoir inflow predictions with lead-times of several days are essential to the operational planning and scheduling of hydroelectric power system. The demand for quantitative precipitation forecasting (QPF) is increasing in hydropower operation with the dramatic advances in the numerical weather prediction (NWP) models. This paper presents a simple and an effective algorithm for daily reservoir inflow predictions which solicits the observed precipitation, forecasted precipitation from QPF as predictors and discharges in following 1 to 6 days as predicted targets for multilayer perceptron artificial neural networks (MLP-ANNs) modeling. An improved error back-propagation algorithm with self-adaptive learning rate and self-adaptive momentum coefficient is used to make the supervised training procedure more efficient in both time saving and search optimization. Several commonly used error measures are employed to evaluate the performance of the proposed model and the results, compared with that of ARIMA model, show that the proposed model is capable of obtaining satisfactory forecasting not only in goodness of fit but also in generalization. Furthermore, the presented algorithm is integrated into a practical software system which has been severed for daily inflow predictions with lead-times varying from 1 to 6 days of more than twenty reservoirs operated by the Fujian Province Grid Company, China.

  12. Determining effective forecast horizons for multi-purpose reservoirs with short- and long-term operating objectives

    Science.gov (United States)

    Luchner, Jakob; Anghileri, Daniela; Castelletti, Andrea

    2017-04-01

    selection technique. The technique determines the most informative combination in a multi-variate regression model to the optimal reservoir releases based on perfect information at a fixed objective trade-off. The improved reservoir operation is evaluated against optimal reservoir operation conditioned upon perfect information on future disturbances and basic reservoir operation using only the day of the year and the reservoir level. Different objective trade-offs are selected for analyzing resulting differences in improved reservoir operation and selected forecast variables and horizons. For comparison, the effective streamflow forecast horizon determined by the ISA framework is benchmarked against the performances obtained with a deterministic model predictive control (MPC) optimization scheme. Both the ISA framework and the MPC optimization scheme are applied to the real-world case study of Lake Como, Italy, using perfect streamflow forecast information. The principal operation targets for Lake Como are flood control and downstream water supply which makes its operation a suitable case study. Results provide critical feedback to reservoir operators on the use of long-term streamflow forecasts and to the hydro-meteorological forecasting community with respect to the forecast horizon needed from reliable streamflow forecasts.

  13. Reservoir water level forecasting using group method of data handling

    Science.gov (United States)

    Zaji, Amir Hossein; Bonakdari, Hossein; Gharabaghi, Bahram

    2018-06-01

    Accurately forecasted reservoir water level is among the most vital data for efficient reservoir structure design and management. In this study, the group method of data handling is combined with the minimum description length method to develop a very practical and functional model for predicting reservoir water levels. The models' performance is evaluated using two groups of input combinations based on recent days and recent weeks. Four different input combinations are considered in total. The data collected from Chahnimeh#1 Reservoir in eastern Iran are used for model training and validation. To assess the models' applicability in practical situations, the models are made to predict a non-observed dataset for the nearby Chahnimeh#4 Reservoir. According to the results, input combinations (L, L -1) and (L, L -1, L -12) for recent days with root-mean-squared error (RMSE) of 0.3478 and 0.3767, respectively, outperform input combinations (L, L -7) and (L, L -7, L -14) for recent weeks with RMSE of 0.3866 and 0.4378, respectively, with the dataset from https://www.typingclub.com/st. Accordingly, (L, L -1) is selected as the best input combination for making 7-day ahead predictions of reservoir water levels.

  14. Forecast Informed Reservoir Operations: Bringing Science and Decision-Makers Together to Explore Use of Hydrometeorological Forecasts to Support Future Reservoir Operations

    Science.gov (United States)

    Ralph, F. M.; Jasperse, J.

    2017-12-01

    Forecast Informed Reservoir Operations (FIRO) is a proposed strategy that is exploring inorporation of improved hydrometeorological forecasts of land-falling atmospheric rivers on the U.S. West Coast into reservoir operations. The first testbed for this strategy is Lake Mendocino, which is located in the East Fork of the 1485 mi2 Russian River Watershed in northern California. This project is guided by the Lake Mendocino FIRO Steering Committee (SC). The SC is an ad hoc committee that consists of water managers and scientists from several federal, state, and local agencies, and universities who have teamed to evaluate whether current or improved technology and scientific understanding can be utilized to improve water supply reliability, enhance flood mitigation and support recovery of listed salmon for the Russian River of northern California. In 2015, the SC created a detailed work plan, which included a Preliminary Viability Assessment, which has now been completed. The SC developed a vision that operational efficiency would be improved by using forecasts to inform decisions about releasing or storing water. FIRO would use available reservoir storage in an efficient manner by (1) better forecasting inflow (or lack of inflow) with enhanced technology, and (2) adapting operation in real time to meet the need for storage, rather than making storage available just in case it is needed. The envisioned FIRO strategy has the potential to simultaneously improve water supply reliability, flood protection, and ecosystem outcomes through a more efficient use of existing infrastructure while requiring minimal capital improvements in the physical structure of the dam. This presentation will provide an overview of the creation of the FIRO SC and how it operates, and describes the lessons learned through this partnership. Results in the FIRO Preliminary Viability Assessment will be summarized and next steps described.

  15. Multi-data reservoir history matching for enhanced reservoir forecasting and uncertainty quantification

    KAUST Repository

    Katterbauer, Klemens

    2015-04-01

    Reservoir simulations and history matching are critical for fine-tuning reservoir production strategies, improving understanding of the subsurface formation, and forecasting remaining reserves. Production data have long been incorporated for adjusting reservoir parameters. However, the sparse spatial sampling of this data set has posed a significant challenge for efficiently reducing uncertainty of reservoir parameters. Seismic, electromagnetic, gravity and InSAR techniques have found widespread applications in enhancing exploration for oil and gas and monitoring reservoirs. These data have however been interpreted and analyzed mostly separately, rarely exploiting the synergy effects that could result from combining them. We present a multi-data ensemble Kalman filter-based history matching framework for the simultaneous incorporation of various reservoir data such as seismic, electromagnetics, gravimetry and InSAR for best possible characterization of the reservoir formation. We apply an ensemble-based sensitivity method to evaluate the impact of each observation on the estimated reservoir parameters. Numerical experiments for different test cases demonstrate considerable matching enhancements when integrating all data sets in the history matching process. Results from the sensitivity analysis further suggest that electromagnetic data exhibit the strongest impact on the matching enhancements due to their strong differentiation between water fronts and hydrocarbons in the test cases.

  16. Effect of flow forecasting quality on benefits of reservoir operation - a case study for the Geheyan reservoir (China)

    NARCIS (Netherlands)

    Dong, Xiaohua; Dohmen-Janssen, Catarine M.; Booij, Martijn J.; Hulscher, Suzanne J.M.H.

    2006-01-01

    This paper presents a methodology to determine the effect of flow forecasting quality on the benefits of reservoir operation. The benefits are calculated in terms of the electricity generated, and the quality of the flow forecasting is defined in terms of lead time and accuracy of the forecasts. In

  17. Sub-seasonal-to-seasonal Reservoir Inflow Forecast using Bayesian Hierarchical Hidden Markov Model

    Science.gov (United States)

    Mukhopadhyay, S.; Arumugam, S.

    2017-12-01

    Sub-seasonal-to-seasonal (S2S) (15-90 days) streamflow forecasting is an emerging area of research that provides seamless information for reservoir operation from weather time scales to seasonal time scales. From an operational perspective, sub-seasonal inflow forecasts are highly valuable as these enable water managers to decide short-term releases (15-30 days), while holding water for seasonal needs (e.g., irrigation and municipal supply) and to meet end-of-the-season target storage at a desired level. We propose a Bayesian Hierarchical Hidden Markov Model (BHHMM) to develop S2S inflow forecasts for the Tennessee Valley Area (TVA) reservoir system. Here, the hidden states are predicted by relevant indices that influence the inflows at S2S time scale. The hidden Markov model also captures the both spatial and temporal hierarchy in predictors that operate at S2S time scale with model parameters being estimated as a posterior distribution using a Bayesian framework. We present our work in two steps, namely single site model and multi-site model. For proof of concept, we consider inflows to Douglas Dam, Tennessee, in the single site model. For multisite model we consider reservoirs in the upper Tennessee valley. Streamflow forecasts are issued and updated continuously every day at S2S time scale. We considered precipitation forecasts obtained from NOAA Climate Forecast System (CFSv2) GCM as predictors for developing S2S streamflow forecasts along with relevant indices for predicting hidden states. Spatial dependence of the inflow series of reservoirs are also preserved in the multi-site model. To circumvent the non-normality of the data, we consider the HMM in a Generalized Linear Model setting. Skill of the proposed approach is tested using split sample validation against a traditional multi-site canonical correlation model developed using the same set of predictors. From the posterior distribution of the inflow forecasts, we also highlight different system behavior

  18. Building Adjustable Pre-storm Reservoir Flood-control Release Rules

    Science.gov (United States)

    Yang, Shun-Nien; Chang, Li-Chiu; Chang, Fi-John; Hsieh, Cheng-Daw

    2017-04-01

    Typhoons hit Taiwan several times every year, which could cause serious flood disasters. Because mountainous terrains and steep landforms can rapidly accelerate the speed of flood flow during typhoon events, rivers cannot be a stable source of water supply. Reservoirs become the most effective floodwater storage facilities for alleviating flood damages in Taiwan. The pre-storm flood-control release can significantly increase reservoir storage capacity available to store floodwaters for reducing downstream flood damage, while the uncertainties of total forecasted rainfalls are very high in different stages of an oncoming typhoon, which may cause the risk of water shortage in the future. This study proposes adjustable pre-storm reservoir flood-control release rules in three designed operating stages with various hydrological conditions in the Feitsui Reservoir, a pivot reservoir for water supply to Taipei metropolitan in Taiwan, not only to reduce the risk of reservoir flood control and downstream flooding but also to consider water supply. The three operating stages before an oncoming typhoon are defined upon the timings when: (1) typhoon news is issued (3-7days before typhoon hit); (2) the sea warning is issued (2-4 days before typhoon hit); and (3) the land warning is issued (1-2 days before typhoon hit). We simulate 95 historical typhoon events with 3000 initial water levels and build some pre-storm flood-control release rules to adjust the amount of pre-release based on the total forecasted rainfalls at different operating stages. A great number of simulations (68.4 millions) are conducted to extract their major consequences and then build the adjustable pre-storm reservoir flood-control release rules. Accordingly, given a total forecasted rainfall and a water level, reservoir decision makers can easily identify the corresponding rule to tell the amount of pre-release in any stage. The results show that the proposed adjustable pre-release rules can effectively

  19. Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

    Directory of Open Access Journals (Sweden)

    S. W. D. Turner

    2017-09-01

    Full Text Available Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.

  20. Microchips and controlled-release drug reservoirs.

    Science.gov (United States)

    Staples, Mark

    2010-01-01

    This review summarizes and updates the development of implantable microchip-containing devices that control dosing from drug reservoirs integrated with the devices. As the expense and risk of new drug development continues to increase, technologies that make the best use of existing therapeutics may add significant value. Trends of future medical care that may require advanced drug delivery systems include individualized therapy and the capability to automate drug delivery. Implantable drug delivery devices that promise to address these anticipated needs have been constructed in a variety of ways using micro- and nanoelectromechanical systems (MEMS or NEMS)-based technology. These devices expand treatment options for addressing unmet medical needs related to dosing. Within the last few years, advances in several technologies (MEMS or NEMS fabrication, materials science, polymer chemistry, and data management) have converged to enable the construction of miniaturized implantable devices for controlled delivery of therapeutic agents from one or more reservoirs. Suboptimal performance of conventional dosing methods in terms of safety, efficacy, pain, or convenience can be improved with advanced delivery devices. Microchip-based implantable drug delivery devices allow localized delivery by direct placement of the device at the treatment site, delivery on demand (emergency administration, pulsatile, or adjustable continuous dosing), programmable dosing cycles, automated delivery of multiple drugs, and dosing in response to physiological and diagnostic feedback. In addition, innovative drug-medical device combinations may protect labile active ingredients within hermetically sealed reservoirs. Copyright (c) 2010 John Wiley & Sons, Inc.

  1. Influence of environmental factors on mercury release in hydroelectric reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Morrison, K.; Therien, N.

    1991-04-01

    Due to increased mercury concentrations in fish in hydro-electric reservoirs after flooding, a study was carried out to evaluate the release and transformation of mercury due to vegetation and soil flooded as a result of reservoir creation. Samples of vegetation and soils were immersed in water and concentrations of total mercury, methylmercury and nutrients were followed. The effects of anoxia, pH and temperature on release and transformation were examined. An existing dynamic model of decomposition of flooded materials in reservoirs was modified to include mercury release and transformation, and was calibrated to the experimental data. Amounts of mercury released by the different substrates was of the same order of magnitude. Tree species contributed to the greatest amounts of methylmercury per unit biomass, but the biomass used for these was twigs and foliage. Soil released significant amounts of mercury, but methylation was very low. The model was able to fit well for all substrates except lichen. The model can be adapted to proposed reservoirs to predict nutrient and mecury release and transformation. 175 refs., 38 figs., 38 tabs.

  2. Forecast on Water Locking Damage of Low Permeable Reservoir with Quantum Neural Network

    Science.gov (United States)

    Zhao, Jingyuan; Sun, Yuxue; Feng, Fuping; Zhao, Fulei; Sui, Dianjie; Xu, Jianjun

    2018-01-01

    It is of great importance in oil-gas reservoir protection to timely and correctly forecast the water locking damage, the greatest damage for low permeable reservoir. An analysis is conducted on the production mechanism and various influence factors of water locking damage, based on which a quantum neuron is constructed based on the information processing manner of a biological neuron and the principle of quantum neural algorithm, besides, the quantum neural network model forecasting the water locking of the reservoir is established and related software is also made to forecast the water locking damage of the gas reservoir. This method has overcome the defects of grey correlation analysis that requires evaluation matrix analysis and complicated operation. According to the practice in Longxi Area of Daqing Oilfield, this method is characterized by fast operation, few system parameters and high accuracy rate (the general incidence rate may reach 90%), which can provide reliable support for the protection technique of low permeable reservoir.

  3. Uncertainties in reservoir performance forecasts; Estimativa de incertezas na previsao de desempenho de reservatorios

    Energy Technology Data Exchange (ETDEWEB)

    Loschiavo, Roberto

    1999-07-01

    Project economic evaluation as well as facilities design for oil exploration is, in general based on production forecast. Since production forecast depends on several parameters that are not completely known, one should take a probabilistic approach for reservoir modeling and numerical flow simulation. In this work, we propose a procedure to estimate probabilistic production forecast profiles based on the decision tree technique. The most influencing parameters of a reservoir model are identified identified and combined to generate a number of realizations of the reservoirs. The combination of each branch of the decision tree defines the probability associated to each reservoir model. A computer program was developed to automatically generate the reservoir models, submit them to the numerical simulator, and process the results. Parallel computing was used to improve the performance of the procedure. (author)

  4. The Effect of Model Grid Resolution on the Distributed Hydrologic Simulations for Forecasting Stream Flows and Reservoir Storage

    Science.gov (United States)

    Turnbull, S. J.

    2017-12-01

    Within the US Army Corps of Engineers (USACE), reservoirs are typically operated according to a rule curve that specifies target water levels based on the time of year. The rule curve is intended to maximize flood protection by specifying releases of water before the dominant rainfall period for a region. While some operating allowances are permissible, generally the rule curve elevations must be maintained. While this operational approach provides for the required flood control purpose, it may not result in optimal reservoir operations for multi-use impoundments. In the Russian River Valley of California a multi-agency research effort called Forecast-Informed Reservoir Operations (FIRO) is assessing the application of forecast weather and streamflow predictions to potentially enhance the operation of reservoirs in the watershed. The focus of the study has been on Lake Mendocino, a USACE project important for flood control, water supply, power generation and ecological flows. As part of this effort the Engineer Research and Development Center is assessing the ability of utilizing the physics based, distributed watershed model Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model to simulate stream flows, reservoir stages, and discharges while being driven by weather forecast products. A key question in this application is the effect of watershed model resolution on forecasted stream flows. To help resolve this question, GSSHA models of multiple grid resolutions, 30, 50, and 270m, were developed for the upper Russian River, which includes Lake Mendocino. The models were derived from common inputs: DEM, soils, land use, stream network, reservoir characteristics, and specified inflows and discharges. All the models were calibrated in both event and continuous simulation mode using measured precipitation gages and then driven with the West-WRF atmospheric model in prediction mode to assess the ability of the model to function in short term, less than one week

  5. Reservoir Management using seasonal forecasts in Lake Kariba and Lake Kahora Bassa: Initial results and plans

    CSIR Research Space (South Africa)

    Muchuru, S

    2012-06-01

    Full Text Available Seasonal forecasting as a tool to improve on reservoir management in Zimbabwe is presented. The focus of the talk is on predicting rainfall extremes over the Lake Kariba catchments. The forecast systems to do the predictions and the levels of skill...

  6. Application of the Fokker-Plank-Kolmogorov equation for affluence forecast to hydropower reservoirs (Betania Case)

    International Nuclear Information System (INIS)

    Dominguez Calle, Efrain Antonio

    2004-01-01

    This paper shows a modeling technique to forecast probability density curves for the flows that represent the monthly affluence to hydropower reservoirs. Briefly, the factors that require affluence forecast in terms of probabilities, the ranges of existing forecast methods as well as the contradiction between those techniques and the real requirements of decision-making procedures are pointed out. The mentioned contradiction is resolved applying the Fokker-Planck-Kolmogorov equation that describes the time evolution of a stochastic process that can be considered as markovian. We show the numerical scheme for this equation, its initial and boundary conditions, and its application results in the case of Betania's reservoir

  7. Developing reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information

    Science.gov (United States)

    Yang, Tiantian; Asanjan, Ata Akbari; Welles, Edwin; Gao, Xiaogang; Sorooshian, Soroosh; Liu, Xiaomang

    2017-04-01

    Reservoirs are fundamental human-built infrastructures that collect, store, and deliver fresh surface water in a timely manner for many purposes. Efficient reservoir operation requires policy makers and operators to understand how reservoir inflows are changing under different hydrological and climatic conditions to enable forecast-informed operations. Over the last decade, the uses of Artificial Intelligence and Data Mining [AI & DM] techniques in assisting reservoir streamflow subseasonal to seasonal forecasts have been increasing. In this study, Random Forest [RF), Artificial Neural Network (ANN), and Support Vector Regression (SVR) are employed and compared with respect to their capabilities for predicting 1 month-ahead reservoir inflows for two headwater reservoirs in USA and China. Both current and lagged hydrological information and 17 known climate phenomenon indices, i.e., PDO and ENSO, etc., are selected as predictors for simulating reservoir inflows. Results show (1) three methods are capable of providing monthly reservoir inflows with satisfactory statistics; (2) the results obtained by Random Forest have the best statistical performances compared with the other two methods; (3) another advantage of Random Forest algorithm is its capability of interpreting raw model inputs; (4) climate phenomenon indices are useful in assisting monthly or seasonal forecasts of reservoir inflow; and (5) different climate conditions are autocorrelated with up to several months, and the climatic information and their lags are cross correlated with local hydrological conditions in our case studies.

  8. Daily Reservoir Inflow Forecasting using Deep Learning with Downscaled Multi-General Circulation Models (GCMs) Platform

    Science.gov (United States)

    Li, D.; Fang, N. Z.

    2017-12-01

    Dallas-Fort Worth Metroplex (DFW) has a population of over 7 million depending on many water supply reservoirs. The reservoir inflow plays a vital role in water supply decision making process and long-term strategic planning for the region. This paper demonstrates a method of utilizing deep learning algorithms and multi-general circulation model (GCM) platform to forecast reservoir inflow for three reservoirs within the DFW: Eagle Mountain Lake, Lake Benbrook and Lake Arlington. Ensemble empirical mode decomposition was firstly employed to extract the features, which were then represented by the deep belief networks (DBNs). The first 75 years of the historical data (1940 -2015) were used to train the model, while the last 2 years of the data (2016-2017) were used for the model validation. The weights of each DBN gained from the training process were then applied to establish a neural network (NN) that was able to forecast reservoir inflow. Feature predictors used for the forecasting model were generated from weather forecast results of the downscaled multi-GCM platform for the North Texas region. By comparing root mean square error (RMSE) and mean bias error (MBE) with the observed data, the authors found that the deep learning with downscaled multi-GCM platform is an effective approach in the reservoir inflow forecasting.

  9. Risk Analysis of Reservoir Flood Routing Calculation Based on Inflow Forecast Uncertainty

    Directory of Open Access Journals (Sweden)

    Binquan Li

    2016-10-01

    Full Text Available Possible risks in reservoir flood control and regulation cannot be objectively assessed by deterministic flood forecasts, resulting in the probability of reservoir failure. We demonstrated a risk analysis of reservoir flood routing calculation accounting for inflow forecast uncertainty in a sub-basin of Huaihe River, China. The Xinanjiang model was used to provide deterministic flood forecasts, and was combined with the Hydrologic Uncertainty Processor (HUP to quantify reservoir inflow uncertainty in the probability density function (PDF form. Furthermore, the PDFs of reservoir water level (RWL and the risk rate of RWL exceeding a defined safety control level could be obtained. Results suggested that the median forecast (50th percentiles of HUP showed better agreement with observed inflows than the Xinanjiang model did in terms of the performance measures of flood process, peak, and volume. In addition, most observations (77.2% were bracketed by the uncertainty band of 90% confidence interval, with some small exceptions of high flows. Results proved that this framework of risk analysis could provide not only the deterministic forecasts of inflow and RWL, but also the fundamental uncertainty information (e.g., 90% confidence band for the reservoir flood routing calculation.

  10. Ensemble seasonal forecast of extreme water inflow into a large reservoir

    Directory of Open Access Journals (Sweden)

    A. N. Gelfan

    2015-06-01

    Full Text Available An approach to seasonal ensemble forecast of unregulated water inflow into a large reservoir was developed. The approach is founded on a physically-based semi-distributed hydrological model ECOMAG driven by Monte-Carlo generated ensembles of weather scenarios for a specified lead-time of the forecast (3 months ahead in this study. Case study was carried out for the Cheboksary reservoir (catchment area is 374 000 km2 located on the middle Volga River. Initial watershed conditions on the forecast date (1 March for spring freshet and 1 June for summer low-water period were simulated by the hydrological model forced by daily meteorological observations several months prior to the forecast date. A spatially distributed stochastic weather generator was used to produce time-series of daily weather scenarios for the forecast lead-time. Ensemble of daily water inflow into the reservoir was obtained by driving the ECOMAG model with the generated weather time-series. The proposed ensemble forecast technique was verified on the basis of the hindcast simulations for 29 spring and summer seasons beginning from 1982 (the year of the reservoir filling to capacity to 2010. The verification criteria were used in order to evaluate an ability of the proposed technique to forecast freshet/low-water events of the pre-assigned severity categories.

  11. Ensemble Flow Forecasts for Risk Based Reservoir Operations of Lake Mendocino in Mendocino County, California: A Framework for Objectively Leveraging Weather and Climate Forecasts in a Decision Support Environment

    Science.gov (United States)

    Delaney, C.; Hartman, R. K.; Mendoza, J.; Whitin, B.

    2017-12-01

    Forecast informed reservoir operations (FIRO) is a methodology that incorporates short to mid-range precipitation and flow forecasts to inform the flood operations of reservoirs. The Ensemble Forecast Operations (EFO) alternative is a probabilistic approach of FIRO that incorporates ensemble streamflow predictions (ESPs) made by NOAA's California-Nevada River Forecast Center (CNRFC). With the EFO approach, release decisions are made to manage forecasted risk of reaching critical operational thresholds. A water management model was developed for Lake Mendocino, a 111,000 acre-foot reservoir located near Ukiah, California, to evaluate the viability of the EFO alternative to improve water supply reliability but not increase downstream flood risk. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United States Army Corps of Engineers and is operated for water supply by the Sonoma County Water Agency. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has suffered from water supply reliability issues since 2007. The EFO alternative was simulated using a 26-year (1985-2010) ESP hindcast generated by the CNRFC. The ESP hindcast was developed using Global Ensemble Forecast System version 10 precipitation reforecasts processed with the Hydrologic Ensemble Forecast System to generate daily reforecasts of 61 flow ensemble members for a 15-day forecast horizon. Model simulation results demonstrate that the EFO alternative may improve water supply reliability for Lake Mendocino yet not increase flood risk for downstream areas. The developed operations framework can directly leverage improved skill in the second week of the forecast and is extendable into the S2S time domain given the demonstration of improved skill through a reliable reforecast of adequate historical duration and consistent with operationally available numerical weather predictions.

  12. Real-time dynamic control of the Three Gorges Reservoir by coupling numerical weather rainfall prediction and flood forecasting

    DEFF Research Database (Denmark)

    Wang, Y.; Chen, H.; Rosbjerg, Dan

    2013-01-01

    In reservoir operation improvement of the accuracy of forecast flood inflow and extension of forecast lead-time can effectively be achieved by using rainfall forecasts from numerical weather predictions with a hydrological catchment model. In this study, the Regional Spectrum Model (RSM), which...... is developed by the Japan Meteorological Agency, was used to forecast rainfall with 5 days lead-time in the upper region of the Three Gorges Reservoir (TGR). A conceptual hydrological model, the Xinanjiang Model, has been set up to forecast the inflow flood of TGR by the Ministry of Water Resources Information...... season 2012 as example, real-time dynamic control of the FLWL was implemented by using the forecasted reservoir flood inflow as input. The forecasted inflow with 5 days lead-time rainfall forecast was evaluated by several performance indices, including the mean relative error of the volumetric reservoir...

  13. Wind field forecast for accidental release of radiative materials

    International Nuclear Information System (INIS)

    Kang Ling; Chen Jiayi; Cai Xuhui

    2003-01-01

    A meso-scale wind field forecast model was designed for emergency environmental assessment in case of accidental release of radiative materials from a nuclear power station. Actual practice of the model showed that it runs fast, has wind field prediction function, and the result given is accurate. With meteorological data collected from weather stations, and pre-treated by a wind field diagnostic model, the initial wind fields at different times were inputted as initial values and assimilation fields for the forecasting model. The model, in turn, worked out to forecast meso-scale wind field of 24 hours in a horizontal domain of 205 km x 205 km. And then, the diagnostic model was employed again with the forecasting data to obtain more detail information of disturbed wind field by local terrain in a smaller domain of 20.5 km x 20.5 km, of which the nuclear power station is at the center. Using observation data in January, April, July and October of 1996 over the area of Hangzhou Bay, wind fields in these 4 months were simulated by different assimilation time and number of the weather stations for a sensitive test. Results indicated that the method used here has increased accuracy of the forecasted wind fields. And incorporating diagnostic method with the wind field forecast model has greatly increased efficiency of the wind field forecast for the smaller domain. This model and scheme have been used in Environmental Consequence Assessment System of Nuclear Accident in Qinshan Area

  14. Hybrid Stochastic Forecasting Model for Management of Large Open Water Reservoir with Storage Function

    Science.gov (United States)

    Kozel, Tomas; Stary, Milos

    2017-12-01

    The main advantage of stochastic forecasting is fan of possible value whose deterministic method of forecasting could not give us. Future development of random process is described better by stochastic then deterministic forecasting. Discharge in measurement profile could be categorized as random process. Content of article is construction and application of forecasting model for managed large open water reservoir with supply function. Model is based on neural networks (NS) and zone models, which forecasting values of average monthly flow from inputs values of average monthly flow, learned neural network and random numbers. Part of data was sorted to one moving zone. The zone is created around last measurement average monthly flow. Matrix of correlation was assembled only from data belonging to zone. The model was compiled for forecast of 1 to 12 month with using backward month flows (NS inputs) from 2 to 11 months for model construction. Data was got ridded of asymmetry with help of Box-Cox rule (Box, Cox, 1964), value r was found by optimization. In next step were data transform to standard normal distribution. The data were with monthly step and forecast is not recurring. 90 years long real flow series was used for compile of the model. First 75 years were used for calibration of model (matrix input-output relationship), last 15 years were used only for validation. Outputs of model were compared with real flow series. For comparison between real flow series (100% successfully of forecast) and forecasts, was used application to management of artificially made reservoir. Course of water reservoir management using Genetic algorithm (GE) + real flow series was compared with Fuzzy model (Fuzzy) + forecast made by Moving zone model. During evaluation process was founding the best size of zone. Results show that the highest number of input did not give the best results and ideal size of zone is in interval from 25 to 35, when course of management was almost same for

  15. Production forecasting and economic evaluation of horizontal wells completed in natural fractured reservoirs

    International Nuclear Information System (INIS)

    Evans, R. D.

    1996-01-01

    A technique for optimizing recovery of hydrocarbons from naturally fractured reservoirs using horizontal well technology was proposed. The technique combines inflow performance analysis, production forecasting and economic considerations, and is based on material balance analysis and linear approximations of reservoir fluid properties as functions of reservoir pressure. An economic evaluation model accounting for the time value of cash flow, interest and inflation rates, is part of the package. Examples of using the technique have been demonstrated. The method is also applied to a gas well producing from a horizontal wellbore intersecting discrete natural fractures. 11 refs., 2 tabs,. 10 figs

  16. Stochastic nonlinear time series forecasting using time-delay reservoir computers: performance and universality.

    Science.gov (United States)

    Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

    2014-07-01

    Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay differential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We tackle some problems associated to the lack of task-universality for individually operating reservoirs and propose a solution based on the use of parallel arrays of time-delay reservoirs. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts

    Science.gov (United States)

    Lu, Mengqian; Lall, Upmanu; Robertson, Andrew W.; Cook, Edward

    2017-03-01

    Streamflow forecasts at multiple time scales provide a new opportunity for reservoir management to address competing objectives. Market instruments such as forward contracts with specified reliability are considered as a tool that may help address the perceived risk associated with the use of such forecasts in lieu of traditional operation and allocation strategies. A water allocation process that enables multiple contracts for water supply and hydropower production with different durations, while maintaining a prescribed level of flood risk reduction, is presented. The allocation process is supported by an optimization model that considers multitime scale ensemble forecasts of monthly streamflow and flood volume over the upcoming season and year, the desired reliability and pricing of proposed contracts for hydropower and water supply. It solves for the size of contracts at each reliability level that can be allocated for each future period, while meeting target end of period reservoir storage with a prescribed reliability. The contracts may be insurable, given that their reliability is verified through retrospective modeling. The process can allow reservoir operators to overcome their concerns as to the appropriate skill of probabilistic forecasts, while providing water users with short-term and long-term guarantees as to how much water or energy they may be allocated. An application of the optimization model to the Bhakra Dam, India, provides an illustration of the process. The issues of forecast skill and contract performance are examined. A field engagement of the idea is useful to develop a real-world perspective and needs a suitable institutional environment.

  18. Forecasting monthly inflow discharge of the Iffezheim reservoir using data-driven models

    Science.gov (United States)

    Zhang, Qing; Aljoumani, Basem; Hillebrand, Gudrun; Hoffmann, Thomas; Hinkelmann, Reinhard

    2017-04-01

    River stream flow is an essential element in hydrology study fields, especially for reservoir management, since it defines input into reservoirs. Forecasting this stream flow plays an important role in short or long-term planning and management in the reservoir, e.g. optimized reservoir and hydroelectric operation or agricultural irrigation. Highly accurate flow forecasting can significantly reduce economic losses and is always pursued by reservoir operators. Therefore, hydrologic time series forecasting has received tremendous attention of researchers. Many models have been proposed to improve the hydrological forecasting. Due to the fact that most natural phenomena occurring in environmental systems appear to behave in random or probabilistic ways, different cases may need a different methods to forecast the inflow and even a unique treatment to improve the forecast accuracy. The purpose of this study is to determine an appropriate model for forecasting monthly inflow to the Iffezheim reservoir in Germany, which is the last of the barrages in the Upper Rhine. Monthly time series of discharges, measured from 1946 to 2001 at the Plittersdorf station, which is located 6 km downstream of the Iffezheim reservoir, were applied. The accuracies of the used stochastic models - Fiering model and Auto-Regressive Integrated Moving Average models (ARIMA) are compared with Artificial Intelligence (AI) models - single Artificial Neural Network (ANN) and Wavelet ANN models (WANN). The Fiering model is a linear stochastic model and used for generating synthetic monthly data. The basic idea in modeling time series using ARIMA is to identify a simple model with as few model parameters as possible in order to provide a good statistical fit to the data. To identify and fit the ARIMA models, four phase approaches were used: identification, parameter estimation, diagnostic checking, and forecasting. An automatic selection criterion, such as the Akaike information criterion, is utilized

  19. Estimating Reservoir Inflow Using RADAR Forecasted Precipitation and Adaptive Neuro Fuzzy Inference System

    Science.gov (United States)

    Yi, J.; Choi, C.

    2014-12-01

    Rainfall observation and forecasting using remote sensing such as RADAR(Radio Detection and Ranging) and satellite images are widely used to delineate the increased damage by rapid weather changeslike regional storm and flash flood. The flood runoff was calculated by using adaptive neuro-fuzzy inference system, the data driven models and MAPLE(McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as the input variables.The result of flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated by comparing it with the actual data.The Adaptive Neuro Fuzzy method was applied to the Chungju Reservoir basin in Korea. The six rainfall events during the flood seasons in 2010 and 2011 were used for the input data.The reservoir inflow estimation results were comparedaccording to the rainfall data used for training, checking and testing data in the model setup process. The results of the 15 models with the combination of the input variables were compared and analyzed. Using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation in this study.The model using the MAPLE forecasted precipitation data showed better result for inflow estimation in the Chungju Reservoir.

  20. EMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirs

    KAUST Repository

    Katterbauer, Klemens

    2014-10-01

    New developments of electromagnetic and seismic techniques have recently revolutionized the oil and gas industry. Time-lapse seismic data is providing engineers with tools to more accurately track the dynamics of multi-phase reservoir fluid flows. With the challenges faced in distinguishing between hydrocarbons and water via seismic methods, the industry has been looking at electromagnetic techniques in order to exploit the strong contrast in conductivity between hydrocarbons and water. Incorporating this information into reservoir simulation is expected to considerably enhance the forecasting of the reservoir, hence optimizing production and reducing costs. Conventional approaches typically invert the seismic and electromagnetic data in order to transform them into production parameters, before incorporating them as constraints in the history matching process and reservoir simulations. This makes automatization difficult and computationally expensive due to the necessity of manual processing, besides the potential artifacts. Here we introduce a new approach to incorporate seismic and electromagnetic data attributes directly into the history matching process. To avoid solving inverse problems and exploit information in the dynamics of the flow, we exploit petrophysical transformations to simultaneously incorporate time lapse seismic and electromagnetic data attributes using different ensemble Kalman-based history matching techniques. Our simulation results show enhanced predictability of the critical reservoir parameters and reduce uncertainties in model simulations, outperforming with only production data or the inclusion of either seismic or electromagnetic data. A statistical test is performed to confirm the significance of the results. © 2014 Elsevier B.V. All rights reserved.

  1. A statistical data assimilation method for seasonal streamflow forecasting to optimize hydropower reservoir management in data-scarce regions

    Science.gov (United States)

    Arsenault, R.; Mai, J.; Latraverse, M.; Tolson, B.

    2017-12-01

    Probabilistic ensemble forecasts generated by the ensemble streamflow prediction (ESP) methodology are subject to biases due to errors in the hydrological model's initial states. In day-to-day operations, hydrologists must compensate for discrepancies between observed and simulated states such as streamflow. However, in data-scarce regions, little to no information is available to guide the streamflow assimilation process. The manual assimilation process can then lead to more uncertainty due to the numerous options available to the forecaster. Furthermore, the model's mass balance may be compromised and could affect future forecasts. In this study we propose a data-driven approach in which specific variables that may be adjusted during assimilation are defined. The underlying principle was to identify key variables that would be the most appropriate to modify during streamflow assimilation depending on the initial conditions such as the time period of the assimilation, the snow water equivalent of the snowpack and meteorological conditions. The variables to adjust were determined by performing an automatic variational data assimilation on individual (or combinations of) model state variables and meteorological forcing. The assimilation aimed to simultaneously optimize: (1) the error between the observed and simulated streamflow at the timepoint where the forecasts starts and (2) the bias between medium to long-term observed and simulated flows, which were simulated by running the model with the observed meteorological data on a hindcast period. The optimal variables were then classified according to the initial conditions at the time period where the forecast is initiated. The proposed method was evaluated by measuring the average electricity generation of a hydropower complex in Québec, Canada driven by this method. A test-bed which simulates the real-world assimilation, forecasting, water release optimization and decision-making of a hydropower cascade was

  2. Reservoir release patterns for hydropower operations at the Aspinall Unit on the Gunnison River, Colorado

    International Nuclear Information System (INIS)

    Yin, S.C.L.; Sedlacek, J.

    1995-05-01

    This report presents the development of reservoir release patterns for the Aspinall Unit, which includes Blue Mesa, Morrow Point, and Crystal Reservoirs on the Gunnison River in Colorado. Release patterns were assessed for two hydropower operational scenarios--seasonally adjusted steady flows and seasonally adjusted high fluctuating flows--and three representative hydrologic years--moderate (1987), dry (1989), and wet (1983). The release patterns for the operational scenarios were developed with the aid of monthly, daily, and hourly reservoir operational models, which simulate the linked operation of the three Aspinall Unit reservoirs. Also presented are reservoir fluctuations and downstream water surface elevations corresponding to the reservoir release patterns. Both of the hydropower operational scenarios evaluated are based on the ecological research flows proposed by the US Fish and Wildlife Service for the Aspinall Unit. The first operational scenario allows only seasonally adjusted steady flows (no hourly fluctuations at any dam within one day), whereas the second scenario permits high fluctuating flows from Blue Mesa and Morrow Point Reservoirs during certain times of the year. Crystal Reservoir would release a steady flow within each day under both operational scenarios

  3. Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios

    Science.gov (United States)

    Gelfan, Alexander; Moreydo, Vsevolod; Motovilov, Yury; Solomatine, Dimitri P.

    2018-04-01

    A long-term forecasting ensemble methodology, applied to water inflows into the Cheboksary Reservoir (Russia), is presented. The methodology is based on a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics) that allows for the calculation of an ensemble of inflow hydrographs using two different sets of weather ensembles for the lead time period: observed weather data, constructed on the basis of the Ensemble Streamflow Prediction methodology (ESP-based forecast), and synthetic weather data, simulated by a multi-site weather generator (WG-based forecast). We have studied the following: (1) whether there is any advantage of the developed ensemble forecasts in comparison with the currently issued operational forecasts of water inflow into the Cheboksary Reservoir, and (2) whether there is any noticeable improvement in probabilistic forecasts when using the WG-simulated ensemble compared to the ESP-based ensemble. We have found that for a 35-year period beginning from the reservoir filling in 1982, both continuous and binary model-based ensemble forecasts (issued in the deterministic form) outperform the operational forecasts of the April-June inflow volume actually used and, additionally, provide acceptable forecasts of additional water regime characteristics besides the inflow volume. We have also demonstrated that the model performance measures (in the verification period) obtained from the WG-based probabilistic forecasts, which are based on a large number of possible weather scenarios, appeared to be more statistically reliable than the corresponding measures calculated from the ESP-based forecasts based on the observed weather scenarios.

  4. Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios

    Directory of Open Access Journals (Sweden)

    A. Gelfan

    2018-04-01

    Full Text Available A long-term forecasting ensemble methodology, applied to water inflows into the Cheboksary Reservoir (Russia, is presented. The methodology is based on a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics that allows for the calculation of an ensemble of inflow hydrographs using two different sets of weather ensembles for the lead time period: observed weather data, constructed on the basis of the Ensemble Streamflow Prediction methodology (ESP-based forecast, and synthetic weather data, simulated by a multi-site weather generator (WG-based forecast. We have studied the following: (1 whether there is any advantage of the developed ensemble forecasts in comparison with the currently issued operational forecasts of water inflow into the Cheboksary Reservoir, and (2 whether there is any noticeable improvement in probabilistic forecasts when using the WG-simulated ensemble compared to the ESP-based ensemble. We have found that for a 35-year period beginning from the reservoir filling in 1982, both continuous and binary model-based ensemble forecasts (issued in the deterministic form outperform the operational forecasts of the April–June inflow volume actually used and, additionally, provide acceptable forecasts of additional water regime characteristics besides the inflow volume. We have also demonstrated that the model performance measures (in the verification period obtained from the WG-based probabilistic forecasts, which are based on a large number of possible weather scenarios, appeared to be more statistically reliable than the corresponding measures calculated from the ESP-based forecasts based on the observed weather scenarios.

  5. Effect of heterogeneity in a horizontal well with multiple fractures on the long term forecast in shale gas reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Nobakht, M.; Ambrose, R.; Clarkson, C.R. [Society of Petroleum Engineers (Canada)

    2011-07-01

    Multiple fracture horizontal wells (MFHWs) are the most popular type of method used for exploiting shale gas reservoirs. When analyzing MFHW's a homogeneous completion model is often used, but this rarely occurs in the field. This paper develops a hybrid method for forecasting MFHWs based on a heterogeneous completion and investigates the effect of completion heterogeneity on production forecasts. First, a current forecasting method for homogeneous completions was modified for heterogeneous completions. The new forecasting method was then validated using a numerical simulation. A relationship between Arps' hyperbolic decline exponent and the heterogeneity of a completion for a particular case was then developed. Lastly, a field case was analyzed to compare the impact of forecasting with and without taking a heterogeneous completion into consideration. Through analysis and simulations this paper found that the long-term forecast of MFHWs can be greatly impacted should heterogeneity of the completion be ignored.

  6. Reservoir operation using El Niño forecasts-case study of Daule Peripa and Baba, Ecuador

    DEFF Research Database (Denmark)

    Gelati, Emiliano; Madsen, Henrik; Rosbjerg, Dan

    2014-01-01

    Reservoir operation is studied for the Daule Peripa and Baba system in Ecuador, where El Niño events cause anomalously heavy precipitation. Reservoir inflow is modelled by a Markov-switching model using El Niño-Southern Oscillation (ENSO) indices as input. Inflow is forecast using 9-month lead time...... Reservoir. Optimized operation is compared to historical management of Daule Peripa. Hypothetical management scenarios are used as the benchmark for the planned system, for which no operation policy is known. Upper bounds for operational performance are found via dynamic programming by assuming perfect...... knowledge of future inflow. The results highlight the advantages of combining inflow forecasts and storage targets in reservoir operation. © 2014 © 2014 IAHS Press....

  7. Advanced productivity forecast using petrophysical wireline data calibrated with MDT tests and numerical reservoir simulation

    Energy Technology Data Exchange (ETDEWEB)

    Andre, Carlos de [PETROBRAS, Rio de Janeiro, RJ (Brazil); Canas, Jesus A.; Low, Steven; Barreto, Wesley [Schlumberger, Houston, TX (United States)

    2004-07-01

    This paper describes an integrated and rigorous approach for viscous and middle oil reservoir productivity evaluation using petrophysical models calibrated with permeability derived from mini tests (Dual Packer) and Vertical Interference Tests (VIT) from open hole wire line testers (MDT SLB TM). It describes the process from Dual Packer Test and VIT pre-job design, evaluation via analytical and inverse simulation modeling, calibration and up scaling of petrophysical data into a numerical model, history matching of Dual Packer Tests and VIT with numerical simulation modeling. Finally, after developing a dynamic calibrated model, we perform productivity forecasts of different well configurations (vertical, horizontal and multilateral wells) for several deep offshore oil reservoirs in order to support well testing activities and future development strategies. The objective was to characterize formation static and dynamic properties early in the field development process to optimize well testing design, extended well test (EWT) and support the development strategies in deep offshore viscous oil reservoirs. This type of oil has limitations to flow naturally to surface and special lifting equipment is required for smooth optimum well testing/production. The integrated analysis gave a good overall picture of the formation, including permeability anisotropy and fluid dynamics. Subsequent analysis of different well configurations and lifting schemes allows maximizing formation productivity. The simulation and calibration results are compared to measured well test data. Results from this work shows that if the various petrophysical and fluid properties sources are integrated properly an accurate well productivity model can be achieved. If done early in the field development program, this time/knowledge gain could reduce the risk and maximize the development profitability of new blocks (value of the information). (author)

  8. A Forecasting Approach Combining Self-Organizing Map with Support Vector Regression for Reservoir Inflow during Typhoon Periods

    Directory of Open Access Journals (Sweden)

    Gwo-Fong Lin

    2016-01-01

    Full Text Available This study describes the development of a reservoir inflow forecasting model for typhoon events to improve short lead-time flood forecasting performance. To strengthen the forecasting ability of the original support vector machines (SVMs model, the self-organizing map (SOM is adopted to group inputs into different clusters in advance of the proposed SOM-SVM model. Two different input methods are proposed for the SVM-based forecasting method, namely, SOM-SVM1 and SOM-SVM2. The methods are applied to an actual reservoir watershed to determine the 1 to 3 h ahead inflow forecasts. For 1, 2, and 3 h ahead forecasts, improvements in mean coefficient of efficiency (MCE due to the clusters obtained from SOM-SVM1 are 21.5%, 18.5%, and 23.0%, respectively. Furthermore, improvement in MCE for SOM-SVM2 is 20.9%, 21.2%, and 35.4%, respectively. Another SOM-SVM2 model increases the SOM-SVM1 model for 1, 2, and 3 h ahead forecasts obtained improvement increases of 0.33%, 2.25%, and 10.08%, respectively. These results show that the performance of the proposed model can provide improved forecasts of hourly inflow, especially in the proposed SOM-SVM2 model. In conclusion, the proposed model, which considers limit and higher related inputs instead of all inputs, can generate better forecasts in different clusters than are generated from the SOM process. The SOM-SVM2 model is recommended as an alternative to the original SVR (Support Vector Regression model because of its accuracy and robustness.

  9. A two-stage method of quantitative flood risk analysis for reservoir real-time operation using ensemble-based hydrologic forecasts

    Science.gov (United States)

    Liu, P.

    2013-12-01

    Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based hydrologic forecasts directly depict the inflows not only the marginal distributions but also their persistence via scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasts as inputs. A method is developed by using the forecast horizon point to divide the future time into two stages, the forecast lead-time and the unpredicted time. The risk within the forecast lead-time is computed based on counting the failure number of forecast scenarios, and the risk in the unpredicted time is estimated using reservoir routing with the design floods and the reservoir water levels of forecast horizon point. As a result, a two-stage risk analysis method is set up to quantify the entire flood risks by defining the ratio of the number of scenarios that excessive the critical value to the total number of scenarios. The China's Three Gorges Reservoir (TGR) is selected as a case study, where the parameter and precipitation uncertainties are implemented to produce ensemble-based hydrologic forecasts. The Bayesian inference, Markov Chain Monte Carlo, is used to account for the parameter uncertainty. Two reservoir operation schemes, the real operated and scenario optimization, are evaluated for the flood risks and hydropower profits analysis. With the 2010 flood, it is found that the improvement of the hydrologic forecast accuracy is unnecessary to decrease the reservoir real-time operation risk, and most risks are from the forecast lead-time. It is therefore valuable to decrease the avarice of ensemble-based hydrologic forecasts with less bias for a reservoir operational purpose.

  10. Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach

    Science.gov (United States)

    Moeeni, Hamid; Bonakdari, Hossein; Ebtehaj, Isa

    2017-03-01

    Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average (SARIMA) models have been frequently used for predicting river flow. SARIMA models are linear and do not consider the random component of statistical data. To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) and gene expression programming (GEP) models, which is a new hybrid method (SARIMA-GEP). To this end, a four-step process is employed. First, the monthly inflow datasets are pre-processed. Second, the datasets are modelled linearly with SARIMA and in the third stage, the non-linearity of residual series caused by linear modelling is evaluated. After confirming the non-linearity, the residuals are modelled in the fourth step using a gene expression programming (GEP) method. The proposed hybrid model is employed to predict the monthly inflow to the Jamishan Dam in west Iran. Thirty years' worth of site measurements of monthly reservoir dam inflow with extreme seasonal variations are used. The results of this hybrid model (SARIMA-GEP) are compared with SARIMA, GEP, artificial neural network (ANN) and SARIMA-ANN models. The results indicate that the SARIMA-GEP model ( R 2=78.8, VAF =78.8, RMSE =0.89, MAPE =43.4, CRM =0.053) outperforms SARIMA and GEP and SARIMA-ANN ( R 2=68.3, VAF =66.4, RMSE =1.12, MAPE =56.6, CRM =0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid models indicates the superiority of SARIMA-GEP over the SARIMA-ANN model.

  11. Effects of the uncertainty of energy price and water availability forecasts on the operation of Alpine hydropower reservoir systems

    Science.gov (United States)

    Anghileri, D.; Castelletti, A.; Burlando, P.

    2016-12-01

    European energy markets have experienced dramatic changes in the last years because of the massive introduction of Variable Renewable Sources (VRSs), such as wind and solar power sources, in the generation portfolios in many countries. VRSs i) are intermittent, i.e., their production is highly variable and only partially predictable, ii) are characterized by no correlation between production and demand, iii) have negligible costs of production, and iv) have been largely subsidized. These features result in lower energy prices, but, at the same time, in increased price volatility, and in network stability issues, which pose a threat to traditional power sources because of smaller incomes and higher maintenance costs associated to a more flexible operation of power systems. Storage hydropower systems play an important role in compensating production peaks, both in term of excess and shortage of energy. Traditionally, most of the research effort in hydropower reservoir operation has focused on modeling and forecasting reservoir inflow as well as designing reservoir operation accordingly. Nowadays, price variability may be the largest source of uncertainty in the context of hydropower systems, especially when considering medium-to-large reservoirs, whose storage can easily buffer small inflow fluctuations. In this work, we compare the effects of uncertain inflow and energy price forecasts on hydropower production and profitability. By adding noise to historic inflow and price trajectories, we build a set of synthetic forecasts corresponding to different levels of predictability and assess their impact on reservoir operating policies and performances. The study is conducted on different hydropower systems, including storage systems and pumped-storage systems, with different characteristics, e.g., different inflow-capacity ratios. The analysis focuses on Alpine hydropower systems where the hydrological regime ranges from purely ice and snow-melt dominated to mixed snow

  12. Accuracy Enhancement for Forecasting Water Levels of Reservoirs and River Streams Using a Multiple-Input-Pattern Fuzzification Approach

    Directory of Open Access Journals (Sweden)

    Nariman Valizadeh

    2014-01-01

    Full Text Available Water level forecasting is an essential topic in water management affecting reservoir operations and decision making. Recently, modern methods utilizing artificial intelligence, fuzzy logic, and combinations of these techniques have been used in hydrological applications because of their considerable ability to map an input-output pattern without requiring prior knowledge of the criteria influencing the forecasting procedure. The artificial neurofuzzy interface system (ANFIS is one of the most accurate models used in water resource management. Because the membership functions (MFs possess the characteristics of smoothness and mathematical components, each set of input data is able to yield the best result using a certain type of MF in the ANFIS models. The objective of this study is to define the different ANFIS model by applying different types of MFs for each type of input to forecast the water level in two case studies, the Klang Gates Dam and Rantau Panjang station on the Johor river in Malaysia, to compare the traditional ANFIS model with the new introduced one in two different situations, reservoir and stream, showing the new approach outweigh rather than the traditional one in both case studies. This objective is accomplished by evaluating the model fitness and performance in daily forecasting.

  13. Accuracy enhancement for forecasting water levels of reservoirs and river streams using a multiple-input-pattern fuzzification approach.

    Science.gov (United States)

    Valizadeh, Nariman; El-Shafie, Ahmed; Mirzaei, Majid; Galavi, Hadi; Mukhlisin, Muhammad; Jaafar, Othman

    2014-01-01

    Water level forecasting is an essential topic in water management affecting reservoir operations and decision making. Recently, modern methods utilizing artificial intelligence, fuzzy logic, and combinations of these techniques have been used in hydrological applications because of their considerable ability to map an input-output pattern without requiring prior knowledge of the criteria influencing the forecasting procedure. The artificial neurofuzzy interface system (ANFIS) is one of the most accurate models used in water resource management. Because the membership functions (MFs) possess the characteristics of smoothness and mathematical components, each set of input data is able to yield the best result using a certain type of MF in the ANFIS models. The objective of this study is to define the different ANFIS model by applying different types of MFs for each type of input to forecast the water level in two case studies, the Klang Gates Dam and Rantau Panjang station on the Johor river in Malaysia, to compare the traditional ANFIS model with the new introduced one in two different situations, reservoir and stream, showing the new approach outweigh rather than the traditional one in both case studies. This objective is accomplished by evaluating the model fitness and performance in daily forecasting.

  14. Daily Reservoir Runoff Forecasting Method Using Artificial Neural Network Based on Quantum-behaved Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Chun-tian Cheng

    2015-07-01

    Full Text Available Accurate daily runoff forecasting is of great significance for the operation control of hydropower station and power grid. Conventional methods including rainfall-runoff models and statistical techniques usually rely on a number of assumptions, leading to some deviation from the exact results. Artificial neural network (ANN has the advantages of high fault-tolerance, strong nonlinear mapping and learning ability, which provides an effective method for the daily runoff forecasting. However, its training has certain drawbacks such as time-consuming, slow learning speed and easily falling into local optimum, which cannot be ignored in the real world application. In order to overcome the disadvantages of ANN model, the artificial neural network model based on quantum-behaved particle swarm optimization (QPSO, ANN-QPSO for short, is presented for the daily runoff forecasting in this paper, where QPSO was employed to select the synaptic weights and thresholds of ANN, while ANN was used for the prediction. The proposed model can combine the advantages of both QPSO and ANN to enhance the generalization performance of the forecasting model. The methodology is assessed by using the daily runoff data of Hongjiadu reservoir in southeast Guizhou province of China from 2006 to 2014. The results demonstrate that the proposed approach achieves much better forecast accuracy than the basic ANN model, and the QPSO algorithm is an alternative training technique for the ANN parameters selection.

  15. Sparse Bayesian learning machine for real-time management of reservoir releases

    Science.gov (United States)

    Khalil, Abedalrazq; McKee, Mac; Kemblowski, Mariush; Asefa, Tirusew

    2005-11-01

    Water scarcity and uncertainties in forecasting future water availabilities present serious problems for basin-scale water management. These problems create a need for intelligent prediction models that learn and adapt to their environment in order to provide water managers with decision-relevant information related to the operation of river systems. This manuscript presents examples of state-of-the-art techniques for forecasting that combine excellent generalization properties and sparse representation within a Bayesian paradigm. The techniques are demonstrated as decision tools to enhance real-time water management. A relevance vector machine, which is a probabilistic model, has been used in an online fashion to provide confident forecasts given knowledge of some state and exogenous conditions. In practical applications, online algorithms should recognize changes in the input space and account for drift in system behavior. Support vectors machines lend themselves particularly well to the detection of drift and hence to the initiation of adaptation in response to a recognized shift in system structure. The resulting model will normally have a structure and parameterization that suits the information content of the available data. The utility and practicality of this proposed approach have been demonstrated with an application in a real case study involving real-time operation of a reservoir in a river basin in southern Utah.

  16. EMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirs

    KAUST Repository

    Katterbauer, Klemens; Hoteit, Ibrahim; Sun, Shuyu

    2014-01-01

    into production parameters, before incorporating them as constraints in the history matching process and reservoir simulations. This makes automatization difficult and computationally expensive due to the necessity of manual processing, besides the potential

  17. Using a Bayesian Probabilistic Forecasting Model to Analyze the Uncertainty in Real-Time Dynamic Control of the Flood Limiting Water Level for Reservoir Operation

    DEFF Research Database (Denmark)

    Liu, Dedi; Li, Xiang; Guo, Shenglian

    2015-01-01

    Dynamic control of the flood limiting water level (FLWL) is a valuable and effective way to maximize the benefits from reservoir operation without exceeding the design risk. In order to analyze the impacts of input uncertainty, a Bayesian forecasting system (BFS) is adopted. Applying quantile water...... inflow values and their uncertainties obtained from the BFS, the reservoir operation results from different schemes can be analyzed in terms of benefits, dam safety, and downstream impacts during the flood season. When the reservoir FLWL dynamic control operation is implemented, there are two fundamental......, also deterministic water inflow was tested. The proposed model in the paper emphasizes the importance of analyzing the uncertainties of the water inflow forecasting system for real-time dynamic control of the FLWL for reservoir operation. For the case study, the selected quantile inflow from...

  18. Real-Time Flood Control by Tree-Based Model Predictive Control Including Forecast Uncertainty: A Case Study Reservoir in Turkey

    Directory of Open Access Journals (Sweden)

    Gökçen Uysal

    2018-03-01

    Full Text Available Optimal control of reservoirs is a challenging task due to conflicting objectives, complex system structure, and uncertainties in the system. Real time control decisions suffer from streamflow forecast uncertainty. This study aims to use Probabilistic Streamflow Forecasts (PSFs having a lead-time up to 48 h as input for the recurrent reservoir operation problem. A related technique for decision making is multi-stage stochastic optimization using scenario trees, referred to as Tree-based Model Predictive Control (TB-MPC. Deterministic Streamflow Forecasts (DSFs are provided by applying random perturbations on perfect data. PSFs are synthetically generated from DSFs by a new approach which explicitly presents dynamic uncertainty evolution. We assessed different variables in the generation of stochasticity and compared the results using different scenarios. The developed real-time hourly flood control was applied to a test case which had limited reservoir storage and restricted downstream condition. According to hindcasting closed-loop experiment results, TB-MPC outperforms the deterministic counterpart in terms of decreased downstream flood risk according to different independent forecast scenarios. TB-MPC was also tested considering different number of tree branches, forecast horizons, and different inflow conditions. We conclude that using synthetic PSFs in TB-MPC can provide more robust solutions against forecast uncertainty by resolution of uncertainty in trees.

  19. Ensemble hydrological forecast efficiency evolution over various issue dates and lead-time: case study for the Cheboksary reservoir (Volga River)

    Science.gov (United States)

    Gelfan, Alexander; Moreido, Vsevolod

    2017-04-01

    Ensemble hydrological forecasting allows for describing uncertainty caused by variability of meteorological conditions in the river basin for the forecast lead-time. At the same time, in snowmelt-dependent river basins another significant source of uncertainty relates to variability of initial conditions of the basin (snow water equivalent, soil moisture content, etc.) prior to forecast issue. Accurate long-term hydrological forecast is most crucial for large water management systems, such as the Cheboksary reservoir (the catchment area is 374 000 sq.km) located in the Middle Volga river in Russia. Accurate forecasts of water inflow volume, maximum discharge and other flow characteristics are of great value for this basin, especially before the beginning of the spring freshet season that lasts here from April to June. The semi-distributed hydrological model ECOMAG was used to develop long-term ensemble forecast of daily water inflow into the Cheboksary reservoir. To describe variability of the meteorological conditions and construct ensemble of possible weather scenarios for the lead-time of the forecast, two approaches were applied. The first one utilizes 50 weather scenarios observed in the previous years (similar to the ensemble streamflow prediction (ESP) procedure), the second one uses 1000 synthetic scenarios simulated by a stochastic weather generator. We investigated the evolution of forecast uncertainty reduction, expressed as forecast efficiency, over various consequent forecast issue dates and lead time. We analyzed the Nash-Sutcliffe efficiency of inflow hindcasts for the period 1982 to 2016 starting from 1st of March with 15 days frequency for lead-time of 1 to 6 months. This resulted in the forecast efficiency matrix with issue dates versus lead-time that allows for predictability identification of the basin. The matrix was constructed separately for observed and synthetic weather ensembles.

  20. Forecasting of future earthquakes in the northeast region of India considering energy released concept

    Science.gov (United States)

    Zarola, Amit; Sil, Arjun

    2018-04-01

    This study presents the forecasting of time and magnitude size of the next earthquake in the northeast India, using four probability distribution models (Gamma, Lognormal, Weibull and Log-logistic) considering updated earthquake catalog of magnitude Mw ≥ 6.0 that occurred from year 1737-2015 in the study area. On the basis of past seismicity of the region, two types of conditional probabilities have been estimated using their best fit model and respective model parameters. The first conditional probability is the probability of seismic energy (e × 1020 ergs), which is expected to release in the future earthquake, exceeding a certain level of seismic energy (E × 1020 ergs). And the second conditional probability is the probability of seismic energy (a × 1020 ergs/year), which is expected to release per year, exceeding a certain level of seismic energy per year (A × 1020 ergs/year). The logarithm likelihood functions (ln L) were also estimated for all four probability distribution models. A higher value of ln L suggests a better model and a lower value shows a worse model. The time of the future earthquake is forecasted by dividing the total seismic energy expected to release in the future earthquake with the total seismic energy expected to release per year. The epicentre of recently occurred 4 January 2016 Manipur earthquake (M 6.7), 13 April 2016 Myanmar earthquake (M 6.9) and the 24 August 2016 Myanmar earthquake (M 6.8) are located in zone Z.12, zone Z.16 and zone Z.15, respectively and that are the identified seismic source zones in the study area which show that the proposed techniques and models yield good forecasting accuracy.

  1. Matrix and reservoir-type multipurpose vaginal rings for controlled release of dapivirine and levonorgestrel.

    Science.gov (United States)

    Boyd, Peter; Fetherston, Susan M; McCoy, Clare F; Major, Ian; Murphy, Diarmaid J; Kumar, Sandeep; Holt, Jonathon; Brimer, Andrew; Blanda, Wendy; Devlin, Brid; Malcolm, R Karl

    2016-09-10

    A matrix-type silicone elastomer vaginal ring providing 28-day continuous release of dapivirine (DPV) - a lead candidate human immunodeficiency virus type 1 (HIV-1) microbicide compound - has recently demonstrated moderate levels of protection in two Phase III clinical studies. Here, next-generation matrix and reservoir-type silicone elastomer vaginal rings are reported for the first time offering simultaneous and continuous in vitro release of DPV and the contraceptive progestin levonorgestrel (LNG) over a period of between 60 and 180days. For matrix-type vaginal rings comprising initial drug loadings of 100, 150 or 200mg DPV and 0, 16 or 32mg LNG, Day 1 daily DPV release values were between 4132 and 6113μg while Day 60 values ranged from 284 to 454μg. Daily LNG release ranged from 129 to 684μg on Day 1 and 2-91μg on Day 60. Core-type rings comprising one or two drug-loaded cores provided extended duration of in vitro release out to 180days, and maintained daily drug release rates within much narrower windows (either 75-131μg/day or 37-66μg/day for DPV, and either 96-150μg/day or 37-57μg/day for LNG, depending on core ring configuration and ignoring initial lag release effect for LNG) compared with matrix-type rings. The data support the continued development of these devices as multi-purpose prevention technologies (MPTs) for HIV prevention and long-acting contraception. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Forecasting analysis of runoff for reservoir regulation of dams and weirs in terms of hydro power plant operation

    International Nuclear Information System (INIS)

    Maradjieva, Mariana; Nikolov, Nikola

    2008-01-01

    In order to meet the needs of Hydropower Plant (HPP) production new algorithms and software were developed for daily, seasonal, annual and long-term control of the runoff for the design of dam and weirs. This control is carried out for monitored periods from 20 to 50 years. The control depends on economic considerations, namely that the accepted probability of required water power is 90%, i.e. concerning the runoff and in this way for the useful volume of water dams. The research is accomplished by a design with the observations. First the hydrometric stations are selected at the available analogy with the building project and then the correlative connection is found assessed by general and true correlative coefficients. The transferring to the project of the observations for the average annual and average monthly water discharges is made with the coefficient of the analogy. The theoretical probability curves are chosen with a minimum dispersion. By the last curves the average monthly distributions are settled with probability from 2% to 90% by statistical method. During the investigated period of the regulation the volumes of discharge, overflow and shortage are calculated as and the determination for the accepted volume of the reservoir if the normative probability of the need is executed. As well the power output of the HPP and its participation in the coverage of the charge diagram on the peak load, under peak load, daily and nightly part are determined in separate observed or forecasting periods. The upper problems about the design and the operation of HPP, water output, reservoir volume and coverage of the charge diagram are solved by iterations. Practical examples are given for the runoff and for the time forecasting system.

  3. Use of bias correction techniques to improve seasonal forecasts for reservoirs - A case-study in northwestern Mediterranean.

    Science.gov (United States)

    Marcos, Raül; Llasat, Ma Carmen; Quintana-Seguí, Pere; Turco, Marco

    2018-01-01

    In this paper, we have compared different bias correction methodologies to assess whether they could be advantageous for improving the performance of a seasonal prediction model for volume anomalies in the Boadella reservoir (northwestern Mediterranean). The bias correction adjustments have been applied on precipitation and temperature from the European Centre for Middle-range Weather Forecasting System 4 (S4). We have used three bias correction strategies: two linear (mean bias correction, BC, and linear regression, LR) and one non-linear (Model Output Statistics analogs, MOS-analog). The results have been compared with climatology and persistence. The volume-anomaly model is a previously computed Multiple Linear Regression that ingests precipitation, temperature and in-flow anomaly data to simulate monthly volume anomalies. The potential utility for end-users has been assessed using economic value curve areas. We have studied the S4 hindcast period 1981-2010 for each month of the year and up to seven months ahead considering an ensemble of 15 members. We have shown that the MOS-analog and LR bias corrections can improve the original S4. The application to volume anomalies points towards the possibility to introduce bias correction methods as a tool to improve water resource seasonal forecasts in an end-user context of climate services. Particularly, the MOS-analog approach gives generally better results than the other approaches in late autumn and early winter. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. The Adaptive-Clustering and Error-Correction Method for Forecasting Cyanobacteria Blooms in Lakes and Reservoirs

    Directory of Open Access Journals (Sweden)

    Xiao-zhe Bai

    2017-01-01

    Full Text Available Globally, cyanobacteria blooms frequently occur, and effective prediction of cyanobacteria blooms in lakes and reservoirs could constitute an essential proactive strategy for water-resource protection. However, cyanobacteria blooms are very complicated because of the internal stochastic nature of the system evolution and the external uncertainty of the observation data. In this study, an adaptive-clustering algorithm is introduced to obtain some typical operating intervals. In addition, the number of nearest neighbors used for modeling was optimized by particle swarm optimization. Finally, a fuzzy linear regression method based on error-correction was used to revise the model dynamically near the operating point. We found that the combined method can characterize the evolutionary track of cyanobacteria blooms in lakes and reservoirs. The model constructed in this paper is compared to other cyanobacteria-bloom forecasting methods (e.g., phase space reconstruction and traditional-clustering linear regression, and, then, the average relative error and average absolute error are used to compare the accuracies of these models. The results suggest that the proposed model is superior. As such, the newly developed approach achieves more precise predictions, which can be used to prevent the further deterioration of the water environment.

  5. Inductive reasoning and forecasting of population dynamics of Cylindrospermopsis raciborskii in three sub-tropical reservoirs by evolutionary computation.

    Science.gov (United States)

    Recknagel, Friedrich; Orr, Philip T; Cao, Hongqing

    2014-01-01

    Seven-day-ahead forecasting models of Cylindrospermopsis raciborskii in three warm-monomictic and mesotrophic reservoirs in south-east Queensland have been developed by means of water quality data from 1999 to 2010 and the hybrid evolutionary algorithm HEA. Resulting models using all measured variables as inputs as well as models using electronically measurable variables only as inputs forecasted accurately timing of overgrowth of C. raciborskii and matched well high and low magnitudes of observed bloom events with 0.45≤r 2 >0.61 and 0.4≤r 2 >0.57, respectively. The models also revealed relationships and thresholds triggering bloom events that provide valuable information on synergism between water quality conditions and population dynamics of C. raciborskii. Best performing models based on using all measured variables as inputs indicated electrical conductivity (EC) within the range of 206-280mSm -1 as threshold above which fast growth and high abundances of C. raciborskii have been observed for the three lakes. Best models based on electronically measurable variables for the Lakes Wivenhoe and Somerset indicated a water temperature (WT) range of 25.5-32.7°C within which fast growth and high abundances of C. raciborskii can be expected. By contrast the model for Lake Samsonvale highlighted a turbidity (TURB) level of 4.8 NTU as indicator for mass developments of C. raciborskii. Experiments with online measured water quality data of the Lake Wivenhoe from 2007 to 2010 resulted in predictive models with 0.61≤r 2 >0.65 whereby again similar levels of EC and WT have been discovered as thresholds for outgrowth of C. raciborskii. The highest validity of r 2 =0.75 for an in situ data-based model has been achieved after considering time lags for EC by 7 days and dissolved oxygen by 1 day. These time lags have been discovered by a systematic screening of all possible combinations of time lags between 0 and 10 days for all electronically measurable variables. The so

  6. On the Techa’s reservoirs cascade influence on the long-term forecast of the Techa river radioactive contamination

    Directory of Open Access Journals (Sweden)

    S. S. Utkin

    2016-01-01

    Full Text Available In 1949–1956 years, the Techa river was exposed to the intense radioactive contamination, which consequences are not overcome up to now. Currently, the Techa Cascade of Water Reservoirs is the only source of contamination of this river that could be managed. In February 2016 the Chief Executive Officer of the State Corporation “ROSATOM” approved the «Strategic master-plan on the solution of the problems of the Techa Reservoir Cascade» providing a novel look at an issue of remediation of the Techa river. The aim of the article is the implementation of the modern radiation protection system to the existing or potential exposure situations of public residing near the Techa river and an analysis of possible features, events, and processes considered in the longterm forecasts performed in the field of public radiation safety. Although the current radiation state of the Techa River is relatively stable, the task of refining the traditional phenomenological retrospective analysis covering the assessment of the past and current radiation exposure and environmental impacts is considered quite relevant. The Calculation- monitoring complex “TCR-Prognoz” was developed in the framework of the “Strategic Master Plan”. This complex enables to evaluate multivariate scenario calculations resulting in long-term forecasts of radioactive contamination levels in the Techa River and its floodplain, depending on various sets of environmental conditions and anthropogenic factors. Complex radiation surveys to define the detailed character and the time frames of economic activities permitted under the existing radiation safety requirements in the floodplain of the Techa river are recommended to be started after 2020. By this time, the first steady effects associated with the “Strategic Master Plan” implementation will become evident, including those resulting from the efforts aimed at simultaneous minimization of radionuclide

  7. Fundamental Study of Disposition and Release of Methane in a Shale Gas Reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yifeng [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Xiong, Yongliang [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Repository Performance; Criscenti, Louise J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geochemistry; Ho, Tuan Ahn [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geochemistry; Weck, Philippe F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Storage and Transportation Technology; Ilgen, Anastasia G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geochemistry; Matteo, Edward [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Kruichak, Jessica N. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Mills, Melissa M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Dewers, Thomas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geomechanics; Gordon, Margaret E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Materials, Devices and Energy Technologies; Akkutlu, Yucel [Texas A & M Univ., College Station, TX (United States). Dept. of Petroleum Engineering

    2016-09-01

    simulations also indicate that a significant fraction (3 - 35%) of methane deposited in kerogen can potentially become trapped in isolated nanopores and thus not recoverable. We have successfully established experimental capabilities for measuring gas sorption and desorption on shale and model materials under a wide range of physical and chemical conditions. Both low and high pressure measurements show significant sorption of CH4 and CO2 onto clays, implying that methane adsorbed on clay minerals could contribute a significant portion of gas-in-place in an unconventional reservoir. We have also studied the potential impact of the interaction of shale with hydrofracking fluid on gas sorption. We have found that the CH4-CO2 sorption capacity for the reacted sample is systematically lower (by a factor of ~2) than that for the unreacted (raw) sample. This difference in sorption capacity may result from a mineralogical or surface chemistry change of the shale sample induced by fluid-rock interaction. Our results shed a new light on mechanistic understanding gas release and production decline in unconventional reservoirs.

  8. Evaluation of Management of Water Release for Painted Rocks Reservoir, Bitterroot River, Montana, 1984 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Lere, Mark E. (Montana Department of Fish, Wildlife and Parks, Missoula, MT)

    1984-11-01

    Baseline fisheries and habitat data were gathered during 1983 and 1984 to evaluate the effectiveness of supplemental water releases from Painted Rocks Reservoir in improving the fisheries resource in the Bitterroot River. Discharge relationships among main stem gaging stations varied annually and seasonally. Flow relationships in the river were dependent upon rainfall events and the timing and duration of the irrigation season. Daily discharge monitored during the summers of 1983 and 1984 was greater than median values derived at the U.S.G.S. station near Darby. Supplemental water released from Painted Rocks Reservoir totaled 14,476 acre feet in 1983 and 13,958 acre feet in 1984. Approximately 63% of a 5.66 m{sup 3}/sec test release of supplemental water conducted during April, 1984 was lost to irrigation withdrawals and natural phenomena before passing Bell Crossing. A similar loss occurred during a 5.66 m{sup 3}/sec test release conducted in August, 1984. Daily maximum temperature monitored during 1984 in the Bitterroot River averaged 11.0, 12.5, 13.9 and 13.6 C at the Darby, Hamilton, Bell and McClay stations, respectively. Chemical parameters measured in the Bitterroot River were favorable to aquatic life. Population estimates conducted in the Fall, 1983 indicated densities of I+ and older rainbow trout (Salmo gairdneri) were significantly greater in a control section than in a dewatered section (p < 0.20). Numbers of I+ and older brown trout (Salmo trutta) were not significantly different between the control and dewatered sections (p > 0.20). Population and biomass estimates for trout in the control section were 631/km and 154.4 kg/km. In the dewatered section, population and biomass estimates for trout were 253/km and 122.8 kg/km. The growth increments of back-calculated length for rainbow trout averaged 75.6 mm in the control section and 66.9mm in the dewatered section. The growth increments of back-calculated length for brown trout averaged 79.5 mm in the

  9. Evaluating Potential for Large Releases from CO2 Storage Reservoirs: Analogs, Scenarios, and Modeling Needs

    International Nuclear Information System (INIS)

    Birkholzer, Jens; Pruess, Karsten; Lewicki, Jennifer; Tsang, Chin-Fu; Karimjee, Anhar

    2005-01-01

    While the purpose of geologic storage of CO 2 in deep saline formations is to trap greenhouse gases underground, the potential exists for CO 2 to escape from the target reservoir, migrate upward along permeable pathways, and discharge at the land surface. Such discharge is not necessarily a serious concern, as CO 2 is a naturally abundant and relatively benign gas in low concentrations. However, there is a potential risk to health, safety and environment (HSE) in the event that large localized fluxes of CO 2 were to occur at the land surface, especially where CO 2 could accumulate. In this paper, we develop possible scenarios for large CO 2 fluxes based on the analysis of natural analogues, where large releases of gas have been observed. We are particularly interested in scenarios which could generate sudden, possibly self-enhancing, or even eruptive release events. The probability for such events may be low, but the circumstances under which they might occur and potential consequences need to be evaluated in order to design appropriate site selection and risk management strategies. Numerical modeling of hypothetical test cases is needed to determine critical conditions for such events, to evaluate whether such conditions may be possible at designated storage sites, and, if applicable, to evaluate the potential HSE impacts of such events and design appropriate mitigation strategies

  10. Reservoir inflow forecasting with a modified coactive neuro-fuzzy inference system: a case study for a semi-arid region

    Science.gov (United States)

    Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Mohd, Nuruol Syuhadaa; Deo, Ravinesh C.; El-Shafie, Ahmed

    2017-10-01

    Existing forecast models applied for reservoir inflow forecasting encounter several drawbacks, due to the difficulty of the underlying mathematical procedures being to cope with and to mimic the naturalization and stochasticity of the inflow data patterns. In this study, appropriate adjustments to the conventional coactive neuro-fuzzy inference system (CANFIS) method are proposed to improve the mathematical procedure, thus enabling a better detection of the high nonlinearity patterns found in the reservoir inflow training data. This modification includes the updating of the back propagation algorithm, leading to a consequent update of the membership rules and the induction of the centre-weighted set rather than the global weighted set used in feature extraction. The modification also aids in constructing an integrated model that is able to not only detect the nonlinearity in the training data but also the wide range of features within the training data records used to simulate the forecasting model. To demonstrate the model's efficacy, the proposed CANFIS method has been applied to forecast monthly inflow data at Aswan High Dam (AHD), located in southern Egypt. Comparative analyses of the forecasting skill of the modified CANFIS and the conventional ANFIS model are carried out with statistical score indicators to assess the reliability of the developed method. The statistical metrics support the better performance of the developed CANFIS model, which significantly outperforms the ANFIS model to attain a low relative error value (23%), mean absolute error (1.4 BCM month-1), root mean square error (1.14 BCM month-1), and a relative large coefficient of determination (0.94). The present study ascertains the better utility of the modified CANFIS model in respect to the traditional ANFIS model applied in reservoir inflow forecasting for a semi-arid region.

  11. Forecasting the consequences of accidental releases of radionuclides in the atmosphere from ensemble dispersion modelling

    International Nuclear Information System (INIS)

    Galmarini, S.; Bianconi, R.; Bellasio, R.; Graziani, G.

    2001-01-01

    The RTMOD system is presented as a tool for the intercomparison of long-range dispersion models as well as a system for support of decision making. RTMOD is an internet-based procedure that collects the results of more than 20 models used around the world to predict the transport and deposition of radioactive releases in the atmosphere. It allows the real-time acquisition of model results and their intercomparison. Taking advantage of the availability of several model results, the system can also be used as a tool to support decision making in case of emergency. The new concept of ensemble dispersion modelling is introduced which is the basis for the decision-making application of RTMOD. New statistical parameters are presented that allow gathering the results of several models to produce a single dispersion forecast. The devised parameters are presented and tested on the results of RTMOD exercises

  12. The FAST-T approach for operational, real time, short term hydrological forecasting: Results from the Betania Hydropower Reservoir case study

    Science.gov (United States)

    Domínguez, Efraín; Angarita, Hector; Rosmann, Thomas; Mendez, Zulma; Angulo, Gustavo

    2013-04-01

    A viable quantitative hydrological forecasting service is a combination of technological elements, personnel and knowledge, working together to establish a stable operational cycle of forecasts emission, dissemination and assimilation; hence, the process for establishing such system usually requires significant resources and time to reach an adequate development and integration in order to produce forecasts with acceptable levels of performance. Here are presented the results of this process for the recently implemented Operational Forecast Service for the Betania's Hydropower Reservoir - or SPHEB, located at the Upper-Magdalena River Basin (Colombia). The current scope of the SPHEB includes forecasting of water levels and discharge for the three main streams affluent to the reservoir, for lead times between +1 to +57 hours, and +1 to +10 days. The core of the SPHEB is the Flexible, Adaptive, Simple and Transient Time forecasting approach, namely FAST-T. This comprises of a set of data structures, mathematical kernel, distributed computing and network infrastructure designed to provide seamless real-time operational forecast and automatic model adjustment in case of failures in data transmission or assimilation. Among FAST-T main features are: an autonomous evaluation and detection of the most relevant information for the later configuration of forecasting models; an adaptively linearized mathematical kernel, the optimal adaptive linear combination or OALC, which provides a computationally simple and efficient algorithm for real-time applications; and finally, a meta-model catalog, containing prioritized forecast models at given stream conditions. The SPHEB is at present feed by the fraction of hydrological monitoring network installed at the basin that has telemetric capabilities via NOAA-GOES satellites (8 stages, approximately 47%) with data availability of about a 90% at one hour intervals. However, there is a dense network of 'conventional' hydro

  13. Modeling the wind-fields of accidental releases with an operational regional forecast model

    International Nuclear Information System (INIS)

    Albritton, J.R.; Lee, R.L.; Sugiyama, G.

    1995-01-01

    The Atmospheric Release Advisory Capability (ARAC) is an operational emergency preparedness and response organization supported primarily by the Departments of Energy and Defense. ARAC can provide real-time assessments of atmospheric releases of radioactive materials at any location in the world. ARAC uses robust three-dimensional atmospheric transport and dispersion models, extensive geophysical and dose-factor databases, meteorological data-acquisition systems, and an experienced staff. Although it was originally conceived and developed as an emergency response and assessment service for nuclear accidents, the ARAC system has been adapted to also simulate non-radiological hazardous releases. For example, in 1991 ARAC responded to three major events: the oil fires in Kuwait, the eruption of Mt. Pinatubo in the Philippines, and the herbicide spill into the upper Sacramento River in California. ARAC's operational simulation system, includes two three-dimensional finite-difference models: a diagnostic wind-field scheme, and a Lagrangian particle-in-cell transport and dispersion scheme. The meteorological component of ARAC's real-time response system employs models using real-time data from all available stations near the accident site to generate a wind-field for input to the transport and dispersion model. Here we report on simulation studies of past and potential release sites to show that even in the absence of local meteorological observational data, readily available gridded analysis and forecast data and a prognostic model, the Navy Operational Regional Atmospheric Prediction System, applied at an appropriate grid resolution can successfully simulate complex local flows

  14. Evaluation of Management of Water Releases for Painted Rocks Reservoir, Bitterroot River, Montana, 1983-1986, Final Report.

    Energy Technology Data Exchange (ETDEWEB)

    Spoon, Ronald L. (Montana Department of Fish, Wildlife and Parks, Missoula, MT)

    1987-06-01

    This study was initiated in July, 1983 to develop a water management plan for the release of water purchased from Painted Rocks Reservoir. Releases were designed to provide optimum benefits to the Bitterroot River fishery. Fisheries, habitat, and stream flow information was gathered to evaluate the effectiveness of these supplemental releases in improving trout populations in the Bitterroot River. The study was part of the Northwest Power Planning Council's Fish and Wildlife Program and was funded by the Bonneville Power Administration. This report presents data collected from 1983 through 1986.

  15. [Sediment-water flux and processes of nutrients and gaseous nitrogen release in a China River Reservoir].

    Science.gov (United States)

    Chen, Zhu-hong; Chen, Neng-wang; Wu, Yin-qi; Mo, Qiong-li; Zhou, Xing-peng; Lu, Ting; Tian, Yun

    2014-09-01

    The key processes and fluxes of nutrients (N and P) and gaseous N (N2 and N2O) across the sediment-water interface in a river reservoir (Xipi) of the Jiulong River watershed in southeast China were studied. Intact core sediment incubation of nutrients exchange, in-situ observation and lab incubation of excess dissolved N2 and N2O (products of nitrification, denitrification and Anammox), and determination of physiochemical and microbe parameters were carried out in 2013 for three representative sites along the lacustrine zone of the reservoir. Results showed that ammonium and phosphate were generally released from sediment to overlying water [with averaged fluxes of N (479.8 ± 675.4) mg. (m2. d)-1 and P (4. 56 ± 0.54) mg. (m2 d) -1] , while nitrate and nitrite diffused into the sediment. Flood events in the wet season could introduce a large amount of particulate organic matter that would be trapped by the dam reservoir, resulting in the high release fluxes of ammonium and phosphate observed in the following low-flow season. No clear spatial variation of sediment nutrient release was found in the lacustrine zone of the reservoir. Gaseous N release was dominated by excess dissolved N2 (98% of total), and the N2 flux from sediment was (15.8 ± 12. 5) mg (m2. d) -1. There was a longitudinal and vertical variation of excess dissolved N2, reflecting the combined results of denitrification and Anammox occurring in anoxic sediment and fluvial transport. Nitrification mainly occurred in the lower lacustrine zone, and the enrichment of N2O was likely regulated by the ratio of ammonium to DIN in water.

  16. Nambe Pueblo Water Budget and Forecasting model.

    Energy Technology Data Exchange (ETDEWEB)

    Brainard, James Robert

    2009-10-01

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  17. Tailored ramp-loading via shock release of stepped-density reservoirs

    International Nuclear Information System (INIS)

    Prisbrey, Shon T.; Park, Hye-Sook; Remington, Bruce A.; Cavallo, Robert; May, Mark; Pollaine, Stephen M.; Rudd, Robert; Maddox, Brian; Comley, Andrew; Fried, Larry; Blobaum, Kerri; Wallace, Russ; Wilson, Mike; Swift, David; Satcher, Joe; Kalantar, Dan; Perry, Ted; Giraldez, Emilio; Farrell, Michael; Nikroo, Abbas

    2012-01-01

    The concept of a gradient piston drive has been extended from that of a single component reservoir, such as a high explosive, to that of a multi-component reservoir that utilizes low density foams and large shocks to achieve high pressures (∼3.5 mbar) and controlled pressure vs. time profiles on a driven sample. Simulated and experimental drives shaped through the use of multiple component (including carbonized resorcinol formaldehyde and SiO 2 foam) reservoirs are compared. Individual density layers in a multiple component reservoir are shown to correlate with velocity features in the measured drive which enables the ability to tune a pressure drive by adjusting the components of the reservoir. Pre-shot simulations are shown to be in rough agreement with the data, but post-shot simulations involving the use of simulated plasma drives were needed to achieve an exact match. Results from a multiple component reservoir shot (∼3.5 mbar) at the National Ignition Facility are shown.

  18. Influence of releases from a fresh water reservoir on the hydrochemistry of the Tinto River (SW Spain).

    Science.gov (United States)

    Cánovas, Carlos Ruiz; Olias, Manuel; Vazquez-Suñé, Enric; Ayora, Carlos; Miguel Nieto, Jose

    2012-02-01

    The Tinto River is an extreme case of pollution by acid mine drainage (AMD), with pH values below 3 and high sulphate, metal and metalloid concentrations along its main course. This study evaluates the impact of releases from a freshwater reservoir on the Tinto River, identifying the metal transport mechanisms. This information is needed to understand the water quality evolution in the long term, and involves the comprehension of interactions between AMD sources, freshwaters, particulate matter and sediments. This work proposes a methodology for quantifying the proportions in which the different sources are contributing. The method is based on the mass balance of solutes and accounts for the uncertainty of end-members. The impact of the releases from the Corumbel Reservoir on the hydrochemistry of the Tinto River was significant, accounting up to a 92% of river discharge. These releases provoked a sharp decrease in dissolved metal concentrations, especially for Fe (approximately 1000 fold) due to dilution and precipitation. Cadmium, Zn, Cu, Co, Ni and Al suffered a dilution to a 12-16 fold decrease while Ca, Sr, Na, Pb and Si were less affected (2-4 folds decrease). However, these releases also gave rise to an increase in particulate transport, mainly Fe, As, Cr, Ba, Pb and Ti, due to sediment remobilisation and Fe precipitation. Aluminium, Li, K, Si, Al, Ni and Sr, together with Cu were present in the particulate phase during the discharge peak. The proposed 2-component mixing model revealed the existence of non-conservative behaviour for Al, Ca, Li, Mn, Ni and Si as a consequence of the interactions between the acidic Tinto waters and the clay-rich reservoir sediments during the bottom outlet opening. These results were improved by a 3-component mixing model, introducing a new end-member to account the chemical dissolution of clay-rich sediments by acidic Tinto waters. Copyright © 2011 Elsevier B.V. All rights reserved.

  19. Influence of releases from a fresh water reservoir on the hydrochemistry of the Tinto River (SW Spain)

    International Nuclear Information System (INIS)

    Cánovas, Carlos Ruiz; Olias, Manuel; Vazquez-Suñé, Enric; Ayora, Carlos; Nieto, Jose Miguel

    2012-01-01

    The Tinto River is an extreme case of pollution by acid mine drainage (AMD), with pH values below 3 and high sulphate, metal and metalloid concentrations along its main course. This study evaluates the impact of releases from a freshwater reservoir on the Tinto River, identifying the metal transport mechanisms. This information is needed to understand the water quality evolution in the long term, and involves the comprehension of interactions between AMD sources, freshwaters, particulate matter and sediments. This work proposes a methodology for quantifying the proportions in which the different sources are contributing. The method is based on the mass balance of solutes and accounts for the uncertainty of end-members. The impact of the releases from the Corumbel Reservoir on the hydrochemistry of the Tinto River was significant, accounting up to a 92% of river discharge. These releases provoked a sharp decrease in dissolved metal concentrations, especially for Fe (approximately 1000 fold) due to dilution and precipitation. Cadmium, Zn, Cu, Co, Ni and Al suffered a dilution to a 12–16 fold decrease while Ca, Sr, Na, Pb and Si were less affected (2–4 folds decrease). However, these releases also gave rise to an increase in particulate transport, mainly Fe, As, Cr, Ba, Pb and Ti, due to sediment remobilisation and Fe precipitation. Aluminium, Li, K, Si, Al, Ni and Sr, together with Cu were present in the particulate phase during the discharge peak. The proposed 2-component mixing model revealed the existence of non-conservative behaviour for Al, Ca, Li, Mn, Ni and Si as a consequence of the interactions between the acidic Tinto waters and the clay-rich reservoir sediments during the bottom outlet opening. These results were improved by a 3-component mixing model, introducing a new end-member to account the chemical dissolution of clay-rich sediments by acidic Tinto waters. - Highlights: ► We study the influence of freshwater releases on the acidic Tinto river

  20. Influence of releases from a fresh water reservoir on the hydrochemistry of the Tinto River (SW Spain)

    Energy Technology Data Exchange (ETDEWEB)

    Canovas, Carlos Ruiz, E-mail: carlos.ruiz@dgeo.uhu.es [Institute of Environmental Assessment and Water Research (IDAeA-CSIC). c/Jordi Girona 18-26, 08034 Barcelona (Spain); Department of Geodynamics and Paleontology, University of Huelva, Facultad de Ciencias Experimentales, Avenida 3 de Marzo s/n, 21071 Huelva (Spain); Olias, Manuel [Department of Physical, Chemical and Natural Systems, University Pablo de Olavide. Ctra.de Utrera km 1, 41013, Sevilla (Spain); Vazquez-Sune, Enric; Ayora, Carlos [Institute of Environmental Assessment and Water Research (IDAeA-CSIC). c/Jordi Girona 18-26, 08034 Barcelona (Spain); Nieto, Jose Miguel [Department of Geology, University of Huelva, Facultad de Ciencias Experimentales, Avenida 3 de Marzo s/n, 21071 Huelva (Spain)

    2012-02-01

    The Tinto River is an extreme case of pollution by acid mine drainage (AMD), with pH values below 3 and high sulphate, metal and metalloid concentrations along its main course. This study evaluates the impact of releases from a freshwater reservoir on the Tinto River, identifying the metal transport mechanisms. This information is needed to understand the water quality evolution in the long term, and involves the comprehension of interactions between AMD sources, freshwaters, particulate matter and sediments. This work proposes a methodology for quantifying the proportions in which the different sources are contributing. The method is based on the mass balance of solutes and accounts for the uncertainty of end-members. The impact of the releases from the Corumbel Reservoir on the hydrochemistry of the Tinto River was significant, accounting up to a 92% of river discharge. These releases provoked a sharp decrease in dissolved metal concentrations, especially for Fe (approximately 1000 fold) due to dilution and precipitation. Cadmium, Zn, Cu, Co, Ni and Al suffered a dilution to a 12-16 fold decrease while Ca, Sr, Na, Pb and Si were less affected (2-4 folds decrease). However, these releases also gave rise to an increase in particulate transport, mainly Fe, As, Cr, Ba, Pb and Ti, due to sediment remobilisation and Fe precipitation. Aluminium, Li, K, Si, Al, Ni and Sr, together with Cu were present in the particulate phase during the discharge peak. The proposed 2-component mixing model revealed the existence of non-conservative behaviour for Al, Ca, Li, Mn, Ni and Si as a consequence of the interactions between the acidic Tinto waters and the clay-rich reservoir sediments during the bottom outlet opening. These results were improved by a 3-component mixing model, introducing a new end-member to account the chemical dissolution of clay-rich sediments by acidic Tinto waters. - Highlights: Black-Right-Pointing-Pointer We study the influence of freshwater releases on the

  1. Study of the copepods population in the Oum Er Rbia estuary (Atlantic Moroccan coast): tides and reservoir release effects

    International Nuclear Information System (INIS)

    El Khalki, A.; Moncef, M.

    2007-01-01

    Variation of environmental parameters and copepods population were studied in the Oum Er Rbia estuary (Atlantic - Moroccan coast) according to the seasons, ( August 1995 to August 1997), tides and reservoir release events. Environemental variability influences copepods diversity and abundance. Salinity (5 to 20 g l-1) appears as the main controlling factor. Among the 27 copepod species recorded, only three marine species (Oithona helgolandica, Euterpina acutifrons, Acartia clausi) and one freshwater species (Acanthocyclops robustus) are able to maintain significant populations due to their large degree of tolerance to salinity changes. (author)

  2. Reservoir management

    International Nuclear Information System (INIS)

    Satter, A.; Varnon, J.E.; Hoang, M.T.

    1992-01-01

    A reservoir's life begins with exploration leading to discovery followed by delineation of the reservoir, development of the field, production by primary, secondary and tertiary means, and finally to abandonment. Sound reservoir management is the key to maximizing economic operation of the reservoir throughout its entire life. Technological advances and rapidly increasing computer power are providing tools to better manage reservoirs and are increasing the gap between good and neural reservoir management. The modern reservoir management process involves goal setting, planning, implementing, monitoring, evaluating, and revising plans. Setting a reservoir management strategy requires knowledge of the reservoir, availability of technology, and knowledge of the business, political, and environmental climate. Formulating a comprehensive management plan involves depletion and development strategies, data acquisition and analyses, geological and numerical model studies, production and reserves forecasts, facilities requirements, economic optimization, and management approval. This paper provides management, engineers, geologists, geophysicists, and field operations staff with a better understanding of the practical approach to reservoir management using a multidisciplinary, integrated team approach

  3. Reservoir management

    International Nuclear Information System (INIS)

    Satter, A.; Varnon, J.E.; Hoang, M.T.

    1992-01-01

    A reservoir's life begins with exploration leading to discovery followed by delineation of the reservoir, development of the field, production by primary, secondary and tertiary means, and finally to abandonment. Sound reservoir management is the key to maximizing economic operation of the reservoir throughout its entire life. Technological advances and rapidly increasing computer power are providing tools to better manage reservoirs and are increasing the gap between good and neutral reservoir management. The modern reservoir management process involves goal setting, planning, implementing, monitoring, evaluating, and revising plans. Setting a reservoir management strategy requires knowledge of the reservoir, availability of technology, and knowledge of the business, political, and environmental climate. Formulating a comprehensive management plan involves depletion and development strategies, data acquisition and analyses, geological and numerical model studies, production and reserves forecasts, facilities requirements, economic optimization, and management approval. This paper provides management, engineers geologists, geophysicists, and field operations staff with a better understanding of the practical approach to reservoir management using a multidisciplinary, integrated team approach

  4. Bioturbation/bioirrigation effect on thallium released from reservoir sediment by different organism types.

    Science.gov (United States)

    He, Yi; Men, Bin; Yang, Xiaofang; Wang, Dongsheng

    2015-11-01

    Bioturbation can remobilize heavy metal in the sediments and may pose a risk for aquatic biota. The effects of bioturbation/bioirrigation by three different riverine organism types (Tubificid, Chironomid larvae, and Loach) on thallium release from contaminated sediment (10.0 ± 1.1 mg Tl/kg sediment, dry wt.) were evaluated in this study. The bioturbation by the epibenthos clearly caused an increased turbidity in the overlying water, and the effect was in the order of Loach > Chironomid larvae > Tubificid. A significant release of Tl into the water column via the resuspended sediment particles was observed, especially for Loach. During the first few days, the leaching of dissolved Tl from sediment into water was fast, and the dissolved Tl under bioturbation/bioirrigation was much higher than the control group. However, after 14 days, the bioturbation/bioirrigation process seemed to suppress the release of Tl from the sediment particles to water, especially for sediment with Loach. This may partly be due to the sorption or coprecipitation of Tl simultaneous with the formation of iron and manganese hydrous oxides with increased pH values as a consequence of phytoplankton growth. Linear regression analysis confirmed that both the total and particulate Tl concentrations had good correlations with particulate Fe and Mn concentrations as well as turbidity in the overlying water. Additionally, planktonic bacteria may oxidize the Tl(I) to Tl(III), resulting in a reduced solubility of Tl by which Tl(OH)3 becomes the predominant form of Tl. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. Forecasting water demand using back propagation networks in the operation of reservoirs in the citarum cascade, west java, indonesia

    Directory of Open Access Journals (Sweden)

    Mulya R. Mashudi

    2017-11-01

    Full Text Available This study investigates the use of Neural Networks (NN as a potential means of more accurately forecasting water demand in the Citarum River basin cascade. Neural Networks have the ability to recognise nonlinear patterns when sufficiently trained with historical data. The study constructs a NN model of the cascade, based on Back Propagation Networks (BPN. Data representing physical characteristics and meteorological conditions in the Citarum River basin from 1989 through 1995 were used to train the BPN. Nonlinear activation functions (sigmoid, tangent, and gaussian functions and hidden layers in the BPN were chosen for the study.

  6. Forecasting consequences of accidental release: how reliable are current assessment models

    International Nuclear Information System (INIS)

    Rohwer, P.S.; Hoffman, F.O.; Miller, C.W.

    1983-01-01

    This paper focuses on uncertainties in model output used to assess accidents. We begin by reviewing the historical development of assessment models and the associated interest in uncertainties as these evolutionary processes occurred in the United States. This is followed by a description of the sources of uncertainties in assessment calculations. Types of models appropriate for assessment of accidents are identified. A summary of results from our analysis of uncertainty is provided in results obtained with current methodology for assessing routine and accidental radionuclide releases to the environment. We conclude with discussion of preferred procedures and suggested future directions to improve the state-of-the-art of radiological assessments

  7. Report (summarized) for fiscal 2000 on survey for demonstration of geothermal exploration technologies. Development of exploration method using reservoir bed fluctuation (Theme 5-1. Reservoir fluctuation forecasting technology); 2000 nendo chinetsu tansa gijutsu to kensho chosa hokokusho (yoyaku). Choryuso hendo tansaho kaihatsu - 5-1 (choryuso hendo yosoku gijutsu)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-03-01

    With an objective of developing a method effective to evaluate reservoir beds in the initial stage of development, to maintain output stability of power plants after having started the operation and to extract reservoirs existing in the vicinity of areas that have already been developed, R and D has been performed in relation with a reservoir simulator on post processors for gravity, SP, and resistivity, and on reservoir modeling. This paper summarizes the achievements in fiscal 2000. In developing the resistivity post processor, a prototype was completed. In developing the resistivity post processor for MT/CSAMT method, an analysis code was structured, and an input/output format was discussed. In developing the seismic wave post processor, a seismic wave characteristics fluctuation model was formulated. Regarding the input/output aiding GUI tools, a conceptual design was made. In developing the reservoir modeling technology, production forecasting simulation using a porous model and an MINC model was performed for the Sumikawa area. Based on the result thereof, forecast calculation was carried out on gravity change, resistivity change and natural potential change. (NEDO)

  8. The Solar Reflectance Index as a Tool to Forecast the Heat Released to the Urban Environment: Potentiality and Assessment Issues

    Directory of Open Access Journals (Sweden)

    Alberto Muscio

    2018-02-01

    Full Text Available Overheating of buildings and urban areas is a more and more severe issue in view of global warming combined with increasing urbanization. The thermal behavior of urban surfaces in the hot seasons is the result of a complex balance of construction and environmental parameters such as insulation level, thermal mass, shielding, and solar reflective capability on one side, and ambient conditions on the other side. Regulations makers and the construction industry have favored the use of parameters that allow the forecasting of the interaction between different material properties without the need for complex analyses. Among these, the solar reflectance index (SRI takes into account solar reflectance and thermal emittance to predict the thermal behavior of a surface subjected to solar radiation through a physically rigorous mathematical procedure that considers assigned air and sky temperatures, peak solar irradiance, and wind velocity. The correlation of SRI with the heat released to the urban environment is analyzed in this paper, as well as the sensitivity of its calculation procedure to variation of the input parameters, as possibly induced by the measurement methods used or by the material ageing.

  9. A Time Domain Update Method for Reservoir History Matching of Electromagnetic Data

    KAUST Repository

    Katterbauer, Klemens; Hoteit, Ibrahim; Sun, Shuyu

    2014-01-01

    production forecasts and optimizing reservoir exploitation. Reservoir history matching has played here a key role incorporating production, seismic, electromagnetic and logging data for forecasting the development of reservoirs and its depletion

  10. Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

    Science.gov (United States)

    Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

    2013-12-01

    Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail

  11. Integrating gravimetric and interferometric synthetic aperture radar data for enhancing reservoir history matching of carbonate gas and volatile oil reservoirs

    KAUST Repository

    Katterbauer, Klemens; Arango, Santiago; Sun, Shuyu; Hoteit, Ibrahim

    2016-01-01

    Reservoir history matching is assuming a critical role in understanding reservoir characteristics, tracking water fronts, and forecasting production. While production data have been incorporated for matching reservoir production levels

  12. Sensitivity Analysis of Flow and Temperature Distributions of Density Currents in a River-Reservoir System under Upstream Releases with Different Durations

    Directory of Open Access Journals (Sweden)

    Gang Chen

    2015-11-01

    Full Text Available A calibrated three-dimensional Environmental Fluid Dynamics Code model was applied to simulate unsteady flow patterns and temperature distributions in the Bankhead river-reservoir system in Alabama, USA. A series of sensitivity model runs were performed under daily repeated large releases (DRLRs with different durations (2, 4 and 6 h from Smith Dam Tailrace (SDT when other model input variables were kept unchanged. The density currents in the river-reservoir system form at different reaches, are destroyed at upstream locations due to the flow momentum of the releases, and form again due to solar heating. DRLRs (140 m3/s with longer durations push the bottom cold water further downstream and maintain a cooler bottom water temperature. For the 6-h DRLR, the momentum effect definitely reaches Cordova (~43.7 km from SDT. Positive bottom velocity (density currents moving downstream is achieved 48.4%, 69.0% and 91.1% of the time with an average velocity of 0.017, 0.042 and 0.053 m/s at Cordova for the 2-h, 4-h and 6-h DRLR, respectively. Results show that DRLRs lasting for at least 4 h maintain lower water temperatures at Cordova. When the 4-h and 6-h DRLRs repeat for more than 6 and 10 days, respectively, bottom temperatures at Cordova become lower than those for the constant small release (2.83 m3/s. These large releases overwhelm the mixing effects due to inflow momentum and maintain temperature stratification at Cordova.

  13. [Characteristics of dissolved organic carbon release under inundation from typical grass plants in the water-level fluctuation zone of the Three Gorges Reservoir area].

    Science.gov (United States)

    Tan, Qiu-Xia; Zhu, Boi; Hua, Ke-Ke

    2013-08-01

    The water-level fluctuation zone of the Three Gorges Reservoir (TGR) exposes in spring and summer, then, green plants especially herbaceous plants grow vigorously. In the late of September, water-level fluctuation zone of TGR goes to inundation. Meanwhile, annually accumulated biomass of plant will be submerged for decaying, resulting in organism decomposition and release a large amount of dissolved organic carbon (DOC). This may lead to negative impacts on water environment of TGR. The typical herbaceous plants from water-level fluctuation zone were collected and inundated in the laboratory for dynamic measurements of DOC concentration of overlying water. According to the determination, the DOC release rates and fluxes have been calculated. Results showed that the release process of DOC variation fitted in a parabolic curve. The peak DOC concentrations emerge averagely in the 15th day of inundation, indicating that DOC released quickly with organism decay of herbaceous plant. The release process of DOC could be described by the logarithm equation. There are significant differences between the concentration of DOC (the maximum DOC concentration is 486.88 mg x L(-1) +/- 35.97 mg x L(-1) for Centaurea picris, the minimum is 4.18 mg x L(-1) +/- 1.07 mg x L(-1) for Echinochloacrus galli) and the release amount of DOC (the maximum is 50.54 mg x g(-1) for Centaurea picris, the minimum is 6.51 mg x g(-1) for Polygonum hydropiper) due to different characteristics of plants, especially, the values of C/N of herbaceous plants. The cumulative DOC release quantities during the whole inundation period were significantly correlated with plants' C/N values in linear equations.

  14. Fate and transport of cyanobacteria and associated toxins and taste-and-odor compounds from upstream reservoir releases in the Kansas River, Kansas, September and October 2011

    Science.gov (United States)

    Graham, Jennifer L.; Ziegler, Andrew C.; Loving, Brian L.; Loftin, Keith A.

    2012-01-01

    Cyanobacteria cause a multitude of water-quality concerns, including the potential to produce toxins and taste-and-odor compounds. Toxins and taste-and-odor compounds may cause substantial economic and public health concerns and are of particular interest in lakes, reservoirs, and rivers that are used for drinking-water supply, recreation, or aquaculture. The Kansas River is a primary source of drinking water for about 800,000 people in northeastern Kansas. Water released from Milford Lake to the Kansas River during a toxic cyanobacterial bloom in late August 2011 prompted concerns about cyanobacteria and associated toxins and taste-and-odor compounds in downstream drinking-water supplies. During September and October 2011 water-quality samples were collected to characterize the transport of cyanobacteria and associated compounds from upstream reservoirs to the Kansas River. This study is one of the first to quantitatively document the transport of cyanobacteria and associated compounds during reservoir releases and improves understanding of the fate and transport of cyanotoxins and taste-and-odor compounds downstream from reservoirs. Milford Lake was the only reservoir in the study area with an ongoing cyanobacterial bloom during reservoir releases. Concentrations of cyanobacteria and associated toxins and taste-and-odor compounds in Milford Lake (upstream from the dam) were not necessarily indicative of outflow conditions (below the dam). Total microcystin concentrations, one of the most commonly occurring cyanobacterial toxins, in Milford Lake were 650 to 7,500 times higher than the Kansas Department of Health and Environment guidance level for a public health warning (20 micrograms per liter) for most of September 2011. By comparison, total microcystin concentrations in the Milford Lake outflow generally were less than 10 percent of the concentrations in surface accumulations, and never exceeded 20 micrograms per liter. The Republican River, downstream from

  15. Forecasting of reservoir pressures of oil and gas bearing complexes in northern part of West Siberia for safety oil and gas deposits exploration and development

    Science.gov (United States)

    Gorbunov, P. A.; Vorobyov, S. V.

    2017-10-01

    In the paper the features of reservoir pressures changes in the northern part of West Siberian oil-and gas province are described. This research is based on the results of hydrodynamic studies in prospecting and explorating wells in Yamal-Nenets Autonomous District. In the Cenomanian, Albian, Aptian and in the top of Neocomian deposits, according to the research, reservoir pressure is usually equal to hydrostatic pressure. At the bottom of the Neocomian and Jurassic deposits zones with abnormally high reservoir pressures (AHRP) are distinguished within Gydan and Yamal Peninsula and in the Nadym-Pur-Taz interfluve. Authors performed the unique zoning of the territory of the Yamal-Nenets Autonomous District according to the patterns of changes of reservoir pressures in the section of the sedimentary cover. The performed zoning and structural modeling allow authors to create a set of the initial reservoir pressures maps for the main oil and gas bearing complexes of the northern part of West Siberia. The results of the survey should improve the efficiency of exploration drilling by preventing complications and accidents during this operation in zones with abnormally high reservoir pressures. In addition, the results of the study can be used to estimate gas resources within prospective areas of Yamal-Nenets Autonomous District.

  16. Montmorillonite/Poly (L-Lactide microcomposite spheres as reservoirs of antidepressant drugs and their controlled release property

    Directory of Open Access Journals (Sweden)

    Shalini Rajkumar

    2015-10-01

    Full Text Available This work evaluates intercalation of Nortriptyline (NT and Venlafaxine (VFX in an interlayer gallery of Na+-MMT (Montmorillonite, which was further compounded with Poly (L-Lactide (PLLA to form microcomposite spheres (MPs for oral controlled drug delivery. The XRD patterns, thermal and spectroscopic analyses indicated intercalation of drugs into the MMT interlayer that was stabilized by electrostatic interaction. No significant changes in structural and functional properties of drugs were found in the MMT layers. In vitro drug release studies showed controlled release pattern.

  17. Modeling Reservoir-River Networks in Support of Optimizing Seasonal-Scale Reservoir Operations

    Science.gov (United States)

    Villa, D. L.; Lowry, T. S.; Bier, A.; Barco, J.; Sun, A.

    2011-12-01

    HydroSCOPE (Hydropower Seasonal Concurrent Optimization of Power and the Environment) is a seasonal time-scale tool for scenario analysis and optimization of reservoir-river networks. Developed in MATLAB, HydroSCOPE is an object-oriented model that simulates basin-scale dynamics with an objective of optimizing reservoir operations to maximize revenue from power generation, reliability in the water supply, environmental performance, and flood control. HydroSCOPE is part of a larger toolset that is being developed through a Department of Energy multi-laboratory project. This project's goal is to provide conventional hydropower decision makers with better information to execute their day-ahead and seasonal operations and planning activities by integrating water balance and operational dynamics across a wide range of spatial and temporal scales. This presentation details the modeling approach and functionality of HydroSCOPE. HydroSCOPE consists of a river-reservoir network model and an optimization routine. The river-reservoir network model simulates the heat and water balance of river-reservoir networks for time-scales up to one year. The optimization routine software, DAKOTA (Design Analysis Kit for Optimization and Terascale Applications - dakota.sandia.gov), is seamlessly linked to the network model and is used to optimize daily volumetric releases from the reservoirs to best meet a set of user-defined constraints, such as maximizing revenue while minimizing environmental violations. The network model uses 1-D approximations for both the reservoirs and river reaches and is able to account for surface and sediment heat exchange as well as ice dynamics for both models. The reservoir model also accounts for inflow, density, and withdrawal zone mixing, and diffusive heat exchange. Routing for the river reaches is accomplished using a modified Muskingum-Cunge approach that automatically calculates the internal timestep and sub-reach lengths to match the conditions of

  18. Modeling the Effects of Reservoir Releases on the Bed Material Sediment Flux of the Colorado River in western Colorado and eastern Utah

    Science.gov (United States)

    Pitlick, J.; Bizzi, S.; Schmitt, R. J. P.

    2017-12-01

    Warm-water reaches of the upper Colorado River have historically provided important habitat for four endangered fishes. Over time these habitats have been altered or lost due to reductions in peak flows and sediment loads caused by reservoir operations. In an effort to reverse these trends, controlled reservoir releases are now used to enhance sediment transport and restore channel complexity. In this presentation, we discuss the development of a sediment routing model designed to assess how changes in water and sediment supply can affect the mass balance of sediment. The model is formulated for ten reaches of the Colorado River spanning 250 km where values of bankfull discharge, width, and reach-average slope have been measured. Bed surface grain size distributions (GSDs) have also been measured throughout the study area; these distributions are used as a test of the model, not as input, except as an upstream boundary condition. In modeling fluxes and GSDs, we assume that the bed load transport capacity is determined by local hydraulic conditions and bed surface grain sizes. Estimates of the bankfull bed load transport capacity in each reach are computed for 14 size fractions of the surface bed material, and the fractional transport rates are summed to get the total transport capacity. In the adjacent reach, fluxes of each size fraction from upstream are used to determine the mean grain size, and the fractional transport capacity of that reach. Calculations proceed downstream and illustrate how linked changes in discharge, shear stress and mean grain size affect (1) the total bed load transport capacity, and (2) the size distribution of the bed surface sediment. The results show that model-derived GSDs match measured GSDs very closely, except for two reaches in the lower part of the study area where slope is affected by uplift associated with salt diapirs; here the model significantly overestimates the transport capacity in relation to the supply. Except for these

  19. Cesium accumulation by aquatic organisms at different trophic levels following an experimental release into a small reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Pinder, J.E., E-mail: jepinder@uga.ed [Savannah River Ecology Laboratory, P. O. Drawer E, Aiken, SC 29802 (United States); Hinton, T.G., E-mail: thomas.hinton@irsn.f [Savannah River Ecology Laboratory, P. O. Drawer E, Aiken, SC 29802 (United States); Taylor, B.E., E-mail: TaylorB@dnr.sc.go [Savannah River Ecology Laboratory, P. O. Drawer E, Aiken, SC 29802 (United States); Whicker, F.W., E-mail: ward.whicker@colostate.ed [Department of Environmental and Radiological Health Sciences, Colorado, State University, Fort Collins, CO 80523-1618 (United States)

    2011-03-15

    The rates of accumulation and subsequent loss of stable cesium ({sup 133}Cs) by organisms at different trophic levels within plankton-based and periphyton-based food chains were measured following the addition of {sup 133}Cs into a small reservoir near Aiken, South Carolina, USA. An uptake parameter u (L kg{sup -1} d{sup -1} dry mass) and a loss rate parameter k (d{sup -1}) were estimated for each organism using time-series measurements of {sup 133}Cs concentrations in water and biota, and these parameters were used to estimate maximum concentrations, times to maximum concentrations, and concentration ratios (C{sub r}). The maximum {sup 133}Cs concentrations for plankton, periphyton, the insect larva Chaoborus punctipennis, which feeds on plankton, and the snail Helisoma trivolvis, which feeds on periphyton, occurred within the first 14 days following the addition, whereas the maximum concentrations for the fish species Lepomis macrochirus and Micropterus salmoides occurred after 170 days. The C{sub r} based on dry mass for plankton and C. punctipennis were 1220 L kg{sup -1} and 5570 L kg{sup -1}, respectively, and were less than the C{sub r} of 8630 L kg{sup -1} for periphyton and 47,700 L kg{sup -1} for H. trivolvis. Although the C{sub r} differed between plankton-based and periphyton-based food chains, they displayed similar levels of biomagnification. Biomagnification was also indicated for fish where the C{sub r} for the mostly nonpiscivorous L. macrochirus of 22,600 L kg{sup -1} was three times less than that for mostly piscivorous M. salmoides of 71,500 L kg{sup -1}. Although the C{sub r} for M. salmoides was greater than those for periphyton and H. trivolvis, the maximum {sup 133}Cs concentrations for periphyton and H. trivolvis were greater than that for M. salmoides. - Research highlights: {yields} A simple uptake and loss model described the Cs dynamics in all the various biota. {yields} Concentrations of Cs were greater in periphyton than in plankton

  20. Trade-off analysis of discharge-desiltation-turbidity and ANN analysis on sedimentation of a combined reservoir-reach system under multi-phase and multi-layer conjunctive releasing operation

    Science.gov (United States)

    Huang, Chien-Lin; Hsu, Nien-Sheng; Wei, Chih-Chiang; Yao, Chun-Hao

    2017-10-01

    Multi-objective reservoir operation considering the trade-off of discharge-desiltation-turbidity during typhoons and sediment concentration (SC) simulation modeling are the vital components for sustainable reservoir management. The purposes of this study were (1) to analyze the multi-layer release trade-offs between reservoir desiltation and intake turbidity of downstream purification plants and thus propose a superior conjunctive operation strategy and (2) to develop ANFIS-based (adaptive network-based fuzzy inference system) and RTRLNN-based (real-time recurrent learning neural networks) substitute SC simulation models. To this end, this study proposed a methodology to develop (1) a series of multi-phase and multi-layer sediment-flood conjunctive release modes and (2) a specialized SC numerical model for a combined reservoir-reach system. The conjunctive release modes involve (1) an optimization model where the decision variables are multi-phase reduction/scaling ratios and the timings to generate a superior total release hydrograph for flood control (Phase I: phase prior to flood arrival, Phase II/III: phase prior to/subsequent to peak flow) and (2) a combination method with physical limitations regarding separation of the singular hydrograph into multi-layer release hydrographs for sediment control. This study employed the featured signals obtained from statistical quartiles/sediment duration curve in mesh segmentation, and an iterative optimization model with a sediment unit response matrix and corresponding geophysical-based acceleration factors, for efficient parameter calibration. This research applied the developed methodology to the Shihmen Reservoir basin in Taiwan. The trade-off analytical results using Typhoons Sinlaku and Jangmi as case examples revealed that owing to gravity current and re-suspension effects, Phase I + II can de-silt safely without violating the intake's turbidity limitation before reservoir discharge reaches 2238 m3/s; however

  1. System to forecast health effects in order to determine necessary counter-measures in case an accidental atmospheric release

    International Nuclear Information System (INIS)

    Merchant, T.E.; Parmentier, N.

    1985-01-01

    In most accident situations involving radioactivity, the required data are the quantitative evaluation of the relevant constituents of the release and the dose factors applicable for these constituents. In the problem of an atmospheric release of radioactivity a third group of data also comes into play, the meteorological conditions at the site and time of the accident. The solution to this problem is the construction of a computer code which, by employing acquired compositions of the release as well as physical accident conditions (at the time of the incident), can be effectively run to calculate and present useful dosimetric data. To meet this need, an interactive computer program has been constructed by the Institut de Protection et de Surete Nucleaire of the Commissariat a l'Energie Atomique which calculates the gamut of dosimetric and statistical information for a region of accidental radiological concern. Application of the program is such that it outputs dosimetric information and other important data in a form independent of the site under consideration, allowing, at the same time, the computation of the same information for areas where demographics show them to be of the highest radiological concern. All this is done after requiring minimal user input

  2. Designing adaptive operating rules for a large multi-purpose reservoir

    Science.gov (United States)

    Geressu, Robel; Rougé, Charles; Harou, Julien

    2017-04-01

    Reservoirs whose live storage capacity is large compared with annual inflow have "memory", i.e., their storage levels contain information about past inflows and reservoir operations. Such "long-memory" reservoirs can be found in basins in dry regions such as the Nile River Basin in Africa, the Colorado River Basin in the US, or river basins in Western and Central Asia. There the effects of a dry year have the potential to impact reservoir levels and downstream releases for several subsequent years, prompting tensions in transboundary basins. Yet, current reservoir operation rules in those reservoirs do not reflect this by integrating past climate history and release decisions among the factors that influence operating decisions. This work proposes and demonstrates an adaptive reservoir operating rule that explicitly accounts for the recent history of release decisions, and not only current storage level and near-term inflow forecasts. This implies adding long-term (e.g., multiyear) objectives to the existing short-term (e.g., annual) ones. We apply these operating rules to the Grand Ethiopian Renaissance Dam, a large reservoir under construction on the Blue Nile River. Energy generation has to be balanced with the imperative of releasing enough water in low flow years (e.g., the minimum 1, 2 or 3 year cumulative flow) to avoid tensions with downstream countries, Sudan and Egypt. Maximizing the minimum multi-year releases could be of interest for the Nile problem to minimize the impact on performance of the large High Aswan Dam in Egypt. Objectives include maximizing the average and minimum annual energy generation and maximizing the minimum annual, two year and three year cumulative releases. The system model is tested using 30 stochastically generated streamflow series. One can then derive adaptive release rules depending on the value of one- and two-year total releases with respect to thresholds. Then, there are 3 sets of release rules for the reservoir depending

  3. Incorporating teleconnection information into reservoir operating policies using Stochastic Dynamic Programming and a Hidden Markov Model

    Science.gov (United States)

    Turner, Sean; Galelli, Stefano; Wilcox, Karen

    2015-04-01

    Water reservoir systems are often affected by recurring large-scale ocean-atmospheric anomalies, known as teleconnections, that cause prolonged periods of climatological drought. Accurate forecasts of these events -- at lead times in the order of weeks and months -- may enable reservoir operators to take more effective release decisions to improve the performance of their systems. In practice this might mean a more reliable water supply system, a more profitable hydropower plant or a more sustainable environmental release policy. To this end, climate indices, which represent the oscillation of the ocean-atmospheric system, might be gainfully employed within reservoir operating models that adapt the reservoir operation as a function of the climate condition. This study develops a Stochastic Dynamic Programming (SDP) approach that can incorporate climate indices using a Hidden Markov Model. The model simulates the climatic regime as a hidden state following a Markov chain, with the state transitions driven by variation in climatic indices, such as the Southern Oscillation Index. Time series analysis of recorded streamflow data reveals the parameters of separate autoregressive models that describe the inflow to the reservoir under three representative climate states ("normal", "wet", "dry"). These models then define inflow transition probabilities for use in a classic SDP approach. The key advantage of the Hidden Markov Model is that it allows conditioning the operating policy not only on the reservoir storage and the antecedent inflow, but also on the climate condition, thus potentially allowing adaptability to a broader range of climate conditions. In practice, the reservoir operator would effect a water release tailored to a specific climate state based on available teleconnection data and forecasts. The approach is demonstrated on the operation of a realistic, stylised water reservoir with carry-over capacity in South-East Australia. Here teleconnections relating

  4. Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

    Science.gov (United States)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    either an intermediate forecast between the extremes of the ensemble spread or a manually selected forecast based on a meteorologists advice. 2. Downstream catchments with low influence of weather forecast In downstream catchments with strong human impact on discharge (e.g. by reservoir operation) and large influence of upstream gauge observation quality on forecast quality, the 'overall error' may in most cases be larger than the combination of the 'model error' and an ensemble spread. Therefore, the overall forecast uncertainty bounds are calculated differently: a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. Here, additionally the corresponding inflow hydrograph from all upstream catchments must be used. b) As for an upstream catchment, the uncertainty range is determined by combination of 'model error' and the ensemble member forecasts c) In addition, the 'overall error' is superimposed on the 'lead forecast'. For reasons of consistency, the lead forecast must be based on the same meteorological forecast in the downstream and all upstream catchments. d) From the resulting two uncertainty ranges (one from the ensemble forecast and 'model error', one from the 'lead forecast' and 'overall error'), the envelope is taken as the most prudent uncertainty range. In sum, the uncertainty associated with each forecast run is calculated and communicated to the public in the form of 10% and 90% percentiles. As in part I of this study, the methodology as well as the useful- or uselessness of the resulting uncertainty ranges will be presented and discussed by typical examples.

  5. Performance assessment of deterministic and probabilistic weather predictions for the short-term optimization of a tropical hydropower reservoir

    Science.gov (United States)

    Mainardi Fan, Fernando; Schwanenberg, Dirk; Alvarado, Rodolfo; Assis dos Reis, Alberto; Naumann, Steffi; Collischonn, Walter

    2016-04-01

    Hydropower is the most important electricity source in Brazil. During recent years, it accounted for 60% to 70% of the total electric power supply. Marginal costs of hydropower are lower than for thermal power plants, therefore, there is a strong economic motivation to maximize its share. On the other hand, hydropower depends on the availability of water, which has a natural variability. Its extremes lead to the risks of power production deficits during droughts and safety issues in the reservoir and downstream river reaches during flood events. One building block of the proper management of hydropower assets is the short-term forecast of reservoir inflows as input for an online, event-based optimization of its release strategy. While deterministic forecasts and optimization schemes are the established techniques for the short-term reservoir management, the use of probabilistic ensemble forecasts and stochastic optimization techniques receives growing attention and a number of researches have shown its benefit. The present work shows one of the first hindcasting and closed-loop control experiments for a multi-purpose hydropower reservoir in a tropical region in Brazil. The case study is the hydropower project (HPP) Três Marias, located in southeast Brazil. The HPP reservoir is operated with two main objectives: (i) hydroelectricity generation and (ii) flood control at Pirapora City located 120 km downstream of the dam. In the experiments, precipitation forecasts based on observed data, deterministic and probabilistic forecasts with 50 ensemble members of the ECMWF are used as forcing of the MGB-IPH hydrological model to generate streamflow forecasts over a period of 2 years. The online optimization depends on a deterministic and multi-stage stochastic version of a model predictive control scheme. Results for the perfect forecasts show the potential benefit of the online optimization and indicate a desired forecast lead time of 30 days. In comparison, the use of

  6. Forecasting oilfield economic performance

    International Nuclear Information System (INIS)

    Bradley, M.E.; Wood, A.R.O.

    1994-01-01

    This paper presents a general method for forecasting oilfield economic performance that integrates cost data with operational, reservoir, and financial information. Practices are developed for determining economic limits for an oil field and its components. The economic limits of marginal wells and the role of underground competition receive special attention. Also examined is the influence of oil prices on operating costs. Examples illustrate application of these concepts. Categorization of costs for historical tracking and projections is recommended

  7. Forecast Combinations

    OpenAIRE

    Timmermann, Allan G

    2005-01-01

    Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the d...

  8. Forecast combinations

    OpenAIRE

    Aiolfi, Marco; Capistrán, Carlos; Timmermann, Allan

    2010-01-01

    We consider combinations of subjective survey forecasts and model-based forecasts from linear and non-linear univariate specifications as well as multivariate factor-augmented models. Empirical results suggest that a simple equal-weighted average of survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables and forecast horizons. Additional improvements can in some cases be gained by using a simple equal-weighted average of survey and model-based fore...

  9. Verification of Ensemble Forecasts for the New York City Operations Support Tool

    Science.gov (United States)

    Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

    2012-12-01

    The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble

  10. Climate variability and sedimentation of a hydropower reservoir

    International Nuclear Information System (INIS)

    Riedel, M.

    2008-01-01

    As part of the relicensing of a large Hydroelectric Project in the central Appalachians, large scale watershed and reservoir sedimentation models were developed to forecast potential sedimentation scenarios. The GIS based watershed model was spatially explicit and calibrated to long term observed data. Potential socio/economic development scenarios were used to construct future watershed land cover scenarios. Climatic variability and potential change analysis were used to identify future climate regimes and shifts in precipitation and temperature patterns. Permutations of these development and climate changes were forecasted over 50 years and used to develop sediment yield regimes to the project reservoir. Extensive field work and reservoir survey, including current and wave instrumentation, were used to characterize the project watershed, rivers and reservoir hydrodynamics. A fully 3 dimensional hydrodynamic reservoir sedimentation model was developed for the project and calibrated to observed data. Hydrologic and sedimentation results from watershed forecasting provided boundary conditions for reservoir inputs. The calibrated reservoir model was then used to forecast changes in reservoir sedimentation and storage capacity under different future climate scenarios. Results indicated unique zones of advancing sediment deltas and temporary storage areas. Forecasted changes in reservoir bathymetry and sedimentation patterns were also developed for the various climate change scenarios. The warmer and wetter scenario produced sedimentation impacts similar to extensive development under no climate change. The results of these analyses are being used to develop collaborative watershed and soil conservation partnerships to reduce future soil losses and reservoir sedimentation from projected development. (author)

  11. Integrating a Storage Factor into R-NARX Neural Networks for Flood Forecasts

    Science.gov (United States)

    Chou, Po-Kai; Chang, Li-Chiu; Chang, Fi-John; Shih, Ban-Jwu

    2017-04-01

    Because mountainous terrains and steep landforms rapidly accelerate the speed of flood flow in Taiwan island, accurate multi-step-ahead inflow forecasts during typhoon events for providing reliable information benefiting the decision-makings of reservoir pre-storm release and flood-control operation are considered crucial and challenging. Various types of artificial neural networks (ANNs) have been successfully applied in hydrological fields. This study proposes a recurrent configuration of the nonlinear autoregressive with exogenous inputs (NARX) network, called R-NARX, with various effective inputs to forecast the inflows of the Feitsui Reservoir, a pivot reservoir for water supply to Taipei metropolitan in Taiwan, during typhoon periods. The proposed R-NARX is constructed based on the recurrent neural network (RNN), which is commonly used for modelling nonlinear dynamical systems. A large number of hourly rainfall and inflow data sets collected from 95 historical typhoon events in the last thirty years are used to train, validate and test the models. The potential input variables, including rainfall in previous time steps (one to six hours), cumulative rainfall, the storage factor and the storage function, are assessed, and various models are constructed with their reliability and accuracy being tested. We find that the previous (t-2) rainfall and cumulative rainfall are crucial inputs and the storage factor and the storage function would also improve the forecast accuracy of the models. We demonstrate that the R-NARX model not only can accurately forecast the inflows but also effectively catch the peak flow without adopting observed inflow data during the entire typhoon period. Besides, the model with the storage factor is superior to the model with the storage function, where its improvement can reach 24%. This approach can well model the rainfall-runoff process for the entire flood forecasting period without the use of observed inflow data and can provide

  12. Forecasting Skill

    Science.gov (United States)

    1981-01-01

    for the third and fourth day precipitation forecasts. A marked improvement was shown for the consensus 24 hour precipitation forecast, and small... Zuckerberg (1980) found a small long term skill increase in forecasts of heavy snow events for nine eastern cities. Other National Weather Service...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I

  13. Appropriate flow forecasting for reservoir operation

    NARCIS (Netherlands)

    Dong, Xiaohua

    2005-01-01

    The aim of the study presented in this thesis is to develop and apply a methodology to determine the appropriate model application by including the water management objective explicitly, and to demonstrate its benefits.

  14. Uncertainties in Forecasting Streamflow using Entropy Theory

    Science.gov (United States)

    Cui, H.; Singh, V. P.

    2017-12-01

    Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

  15. Improving reservoir history matching of EM heated heavy oil reservoirs via cross-well seismic tomography

    KAUST Repository

    Katterbauer, Klemens

    2014-01-01

    Enhanced recovery methods have become significant in the industry\\'s drive to increase recovery rates from oil and gas reservoirs. For heavy oil reservoirs, the immobility of the oil at reservoir temperatures, caused by its high viscosity, limits the recovery rates and strains the economic viability of these fields. While thermal recovery methods, such as steam injection or THAI, have extensively been applied in the field, their success has so far been limited due to prohibitive heat losses and the difficulty in controlling the combustion process. Electromagnetic (EM) heating via high-frequency EM radiation has attracted attention due to its wide applicability in different environments, its efficiency, and the improved controllability of the heating process. While becoming a promising technology for heavy oil recovery, its effect on overall reservoir production and fluid displacements are poorly understood. Reservoir history matching has become a vital tool for the oil & gas industry to increase recovery rates. Limited research has been undertaken so far to capture the nonlinear reservoir dynamics and significantly varying flow rates for thermally heated heavy oil reservoir that may notably change production rates and render conventional history matching frameworks more challenging. We present a new history matching framework for EM heated heavy oil reservoirs incorporating cross-well seismic imaging. Interfacing an EM heating solver to a reservoir simulator via Andrade’s equation, we couple the system to an ensemble Kalman filter based history matching framework incorporating a cross-well seismic survey module. With increasing power levels and heating applied to the heavy oil reservoirs, reservoir dynamics change considerably and may lead to widely differing production forecasts and increased uncertainty. We have shown that the incorporation of seismic observations into the EnKF framework can significantly enhance reservoir simulations, decrease forecasting

  16. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

    OpenAIRE

    Jun-He Yang; Ching-Hsue Cheng; Chia-Pan Chan

    2017-01-01

    Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting m...

  17. Load forecasting

    International Nuclear Information System (INIS)

    Mak, H.

    1995-01-01

    Slides used in a presentation at The Power of Change Conference in Vancouver, BC in April 1995 about the changing needs for load forecasting were presented. Technological innovations and population increase were said to be the prime driving forces behind the changing needs in load forecasting. Structural changes, market place changes, electricity supply planning changes, and changes in planning objectives were other factors discussed. It was concluded that load forecasting was a form of information gathering, that provided important market intelligence

  18. Integrated Drought Monitoring and Forecasts for Decision Making in Water and Agricultural Sectors over the Southeastern US under Changing Climate

    Science.gov (United States)

    Arumugam, S.; Mazrooei, A.; Ward, R.

    2017-12-01

    Changing climate arising from structured oscillations such as ENSO and rising temperature poses challenging issues in meeting the increasing water demand (due to population growth) for public supply and agriculture over the Southeast US. This together with infrastructural (e.g., most reservoirs being within-year systems) and operational (e.g., static rule curves) constraints requires an integrated approach that seamlessly monitors and forecasts water and soil moisture conditions to support adaptive decision making in water and agricultural sectors. In this talk, we discuss the utility of an integrated drought management portal that both monitors and forecasts streamflow and soil moisture over the southeast US. The forecasts are continuously developed and updated by forcing monthly-to-seasonal climate forecasts with a land surface model for various target basins. The portal also houses a reservoir allocation model that allows water managers to explore different release policies in meeting the system constraints and target storages conditioned on the forecasts. The talk will also demonstrate how past events (e.g., 2007-2008 drought) could be proactively monitored and managed to improve decision making in water and agricultural sectors over the Southeast US. Challenges in utilizing the portal information from institutional and operational perspectives will also be presented.

  19. Multi Data Reservoir History Matching using the Ensemble Kalman Filter

    KAUST Repository

    Katterbauer, Klemens

    2015-01-01

    Reservoir history matching is becoming increasingly important with the growing demand for higher quality formation characterization and forecasting and the increased complexity and expenses for modern hydrocarbon exploration projects. History

  20. Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

    Science.gov (United States)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge

  1. River Stream-Flow and Zayanderoud Reservoir Operation Modeling Using the Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Saeed Jamali

    2007-12-01

    Full Text Available The Zayanderoud basin is located in the central plateau of Iran. As a result of population increase and agricultural and industrial developments, water demand on this basin has increased extensively. Given the importance of reservoir operation in water resource and management studies, the performance of fuzzy inference system (FIS for Zayanderoud reservoir operation is investigated in this paper. The model of operation consists of two parts. In the first part, the seasonal river stream-flow is forecasted using the fuzzy rule-based system. The southern oscillated index, rain, snow, and discharge are inputs of the model and the seasonal river stream-flow its output. In the second part, the operation model is constructed. The amount of releases is first optimized by a nonlinear optimization model and then the rule curves are extracted using the fuzzy inference system. This model operates on an "if-then" principle, where the "if" is a vector of fuzzy permits and "then" is the fuzzy result. The reservoir storage capacity, inflow, demand, and year condition factor are used as permits. Monthly release is taken as the consequence. The Zayanderoud basin is investigated as a case study. Different performance indices such as reliability, resiliency, and vulnerability are calculated. According to results, FIS works more effectively than the traditional reservoir operation methods such as standard operation policy (SOP or linear regression.

  2. Dynamic Management of Releases for the Delaware River Basin using NYC's Operations Support Tool

    Science.gov (United States)

    Weiss, W.; Wang, L.; Murphy, T.; Muralidhar, D.; Tarrier, B.

    2011-12-01

    The New York City Department of Environmental Protection (DEP) has initiated design of an Operations Support Tool (OST), a state-of-the-art decision support system to provide computational and predictive support for water supply operations and planning. Using an interim version of OST, DEP and the New York State Department of Environmental Conservation (DEC) have developed a provisional, one-year Delaware River Basin reservoir release program to succeed the existing Flexible Flow Management Program (FFMP) which expired on May 31, 2011. The FFMP grew out of the Good Faith Agreement of 1983 among the four Basin states (New York, New Jersey, Pennsylvania, and Delaware) that established modified diversions and flow targets during drought conditions. It provided a set of release schedules as a framework for managing diversions and releases from New York City's Delaware Basin reservoirs in order to support multiple objectives, including water supply, drought mitigation, flood mitigation, tailwaters fisheries, main stem habitat, recreation, and salinity repulsion. The provisional program (OST-FFMP) defines available water based on current Upper Delaware reservoir conditions and probabilistic forecasts of reservoir inflow. Releases are then set based on a set of release schedules keyed to the water availability. Additionally, OST-FFMP attempts to provide enhanced downstream flood protection by making spill mitigation releases to keep the Delaware System reservoirs at a seasonally varying conditional storage objective. The OST-FFMP approach represents a more robust way of managing downstream releases, accounting for predicted future hydrologic conditions by making more water available for release when conditions are forecasted to be wet and protecting water supply reliability when conditions are forecasted to be dry. Further, the dynamic nature of the program allows the release decision to be adjusted as hydrologic conditions change. OST simulations predict that this

  3. Operational Hydrologic Forecasts in the Columbia River Basin

    Science.gov (United States)

    Shrestha, K. Y.; Curry, J. A.; Webster, P. J.; Toma, V. E.; Jelinek, M.

    2013-12-01

    The Columbia River Basin (CRB) covers an area of ~670,000 km2 and stretches across parts of seven U.S. states and one Canadian province. The basin is subject to a variable climate, and moisture stored in snowpack during the winter is typically released in spring and early summer. These releases contribute to rapid increases in flow. A number of impoundments have been constructed on the Columbia River main stem and its tributaries for the purposes of flood control, navigation, irrigation, recreation, and hydropower. Storage reservoirs allow water managers to adjust natural flow patterns to benefit water and energy demands. In the past decade, the complexity of water resource management issues in the basin has amplified the importance of streamflow forecasting. Medium-range (1-10 day) numerical weather forecasts of precipitation and temperature can be used to drive hydrological models. In this work, probabilistic meteorological variables from the European Center for Medium Range Weather Forecasting (ECMWF) are used to force the Variable Infiltration Capacity (VIC) model. Soil textures were obtained from FAO data; vegetation types / land cover information from UMD land cover data; stream networks from USGS HYDRO1k; and elevations from CGIAR version 4 SRTM data. The surface energy balance in 0.25° (~25 km) cells is closed through an iterative process operating at a 6 hour timestep. Output fluxes from a number of cells in the basin are combined through one-dimensional flow routing predicated on assumptions of linearity and time invariance. These combinations lead to daily mean streamflow estimates at key locations throughout the basin. This framework is suitable for ingesting daily numerical weather prediction data, and was calibrated using USGS mean daily streamflow data at the Dalles Dam (TDA). Operational streamflow forecasts in the CRB have been active since October 2012. These are 'naturalized' or unregulated forecasts. In 2013, increases of ~2600 m3/s (~48% of

  4. Exposure Forecaster

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Exposure Forecaster Database (ExpoCastDB) is EPA's database for aggregating chemical exposure information and can be used to help with chemical exposure...

  5. Strategic Forecasting

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen

    2016-01-01

    Purpose: The purpose of this article is to present an overview of the area of strategic forecasting and its research directions and to put forward some ideas for improving management decisions. Design/methodology/approach: This article is conceptual but also informed by the author’s long contact...... and collaboration with various business firms. It starts by presenting an overview of the area and argues that the area is as much a way of thinking as a toolbox of theories and methodologies. It then spells out a number of research directions and ideas for management. Findings: Strategic forecasting is seen...... as a rebirth of long range planning, albeit with new methods and theories. Firms should make the building of strategic forecasting capability a priority. Research limitations/implications: The article subdivides strategic forecasting into three research avenues and suggests avenues for further research efforts...

  6. Multi Data Reservoir History Matching using the Ensemble Kalman Filter

    KAUST Repository

    Katterbauer, Klemens

    2015-05-01

    Reservoir history matching is becoming increasingly important with the growing demand for higher quality formation characterization and forecasting and the increased complexity and expenses for modern hydrocarbon exploration projects. History matching has long been dominated by adjusting reservoir parameters based solely on well data whose spatial sparse sampling has been a challenge for characterizing the flow properties in areas away from the wells. Geophysical data are widely collected nowadays for reservoir monitoring purposes, but has not yet been fully integrated into history matching and forecasting fluid flow. In this thesis, I present a pioneering approach towards incorporating different time-lapse geophysical data together for enhancing reservoir history matching and uncertainty quantification. The thesis provides several approaches to efficiently integrate multiple geophysical data, analyze the sensitivity of the history matches to observation noise, and examine the framework’s performance in several settings, such as the Norne field in Norway. The results demonstrate the significant improvements in reservoir forecasting and characterization and the synergy effects encountered between the different geophysical data. In particular, the joint use of electromagnetic and seismic data improves the accuracy of forecasting fluid properties, and the usage of electromagnetic data has led to considerably better estimates of hydrocarbon fluid components. For volatile oil and gas reservoirs the joint integration of gravimetric and InSAR data has shown to be beneficial in detecting the influx of water and thereby improving the recovery rate. Summarizing, this thesis makes an important contribution towards integrated reservoir management and multiphysics integration for reservoir history matching.

  7. Freshwater Algal Bloom Prediction by Support Vector Machine in Macau Storage Reservoirs

    Directory of Open Access Journals (Sweden)

    Zhengchao Xie

    2012-01-01

    Full Text Available Understanding and predicting dynamic change of algae population in freshwater reservoirs is particularly important, as algae-releasing cyanotoxins are carcinogens that would affect the health of public. However, the high complex nonlinearity of water variables and their interactions makes it difficult to model the growth of algae species. Recently, support vector machine (SVM was reported to have advantages of only requiring a small amount of samples, high degree of prediction accuracy, and long prediction period to solve the nonlinear problems. In this study, the SVM-based prediction and forecast models for phytoplankton abundance in Macau Storage Reservoir (MSR are proposed, in which the water parameters of pH, SiO2, alkalinity, bicarbonate (HCO3 -, dissolved oxygen (DO, total nitrogen (TN, UV254, turbidity, conductivity, nitrate, total nitrogen (TN, orthophosphate (PO4 3−, total phosphorus (TP, suspended solid (SS and total organic carbon (TOC selected from the correlation analysis of the 23 monthly water variables were included, with 8-year (2001–2008 data for training and the most recent 3 years (2009–2011 for testing. The modeling results showed that the prediction and forecast powers were estimated as approximately 0.76 and 0.86, respectively, showing that the SVM is an effective new way that can be used for monitoring algal bloom in drinking water storage reservoir.

  8. Uncertainty analysis of hydro-meteorological forecasts

    OpenAIRE

    Grythe, Karl Kristian; Gao, Yukun

    2010-01-01

    Masteroppgave i informasjons- og kommunikasjonsteknologi 2010 – Universitetet i Agder, Grimstad Meteorological and hydrological forecasts are very important to human’s life which concerns agriculture, industry, transport, etc. The Nordic hydropower industry use and develop hydrological forecasting models to make predictions of rivers steam flow. The quantity of incoming stream flow is important to the electricity production because excessive water in reservoir will cause flood ...

  9. Development of gas and gas condensate reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-12-01

    In the study of gas reservoir development, the first year topics are restricted on reservoir characterization. There are two types of reservoir characterization. One is the reservoir formation characterization and the other is the reservoir fluid characterization. For the reservoir formation characterization, calculation of conditional simulation was compared with that of unconditional simulation. The results of conditional simulation has higher confidence level than the unconditional simulation because conditional simulation considers the sample location as well as distance correlation. In the reservoir fluid characterization, phase behavior calculations revealed that the component grouping is more important than the increase of number of components. From the liquid volume fraction with pressure drop, the phase behavior of reservoir fluid can be estimated. The calculation results of fluid recombination, constant composition expansion, and constant volume depletion are matched very well with the experimental data. In swelling test of the reservoir fluid with lean gas, the accuracy of dew point pressure forecast depends on the component characterization. (author). 28 figs., 10 tabs.

  10. Forecasting metal prices: Do forecasters herd?

    DEFF Research Database (Denmark)

    Pierdzioch, C.; Rulke, J. C.; Stadtmann, G.

    2013-01-01

    We analyze more than 20,000 forecasts of nine metal prices at four different forecast horizons. We document that forecasts are heterogeneous and report that anti-herding appears to be a source of this heterogeneity. Forecaster anti-herding reflects strategic interactions among forecasters...

  11. Sampling from stochastic reservoir models constrained by production data

    Energy Technology Data Exchange (ETDEWEB)

    Hegstad, Bjoern Kaare

    1997-12-31

    When a petroleum reservoir is evaluated, it is important to forecast future production of oil and gas and to assess forecast uncertainty. This is done by defining a stochastic model for the reservoir characteristics, generating realizations from this model and applying a fluid flow simulator to the realizations. The reservoir characteristics define the geometry of the reservoir, initial saturation, petrophysical properties etc. This thesis discusses how to generate realizations constrained by production data, that is to say, the realizations should reproduce the observed production history of the petroleum reservoir within the uncertainty of these data. The topics discussed are: (1) Theoretical framework, (2) History matching, forecasting and forecasting uncertainty, (3) A three-dimensional test case, (4) Modelling transmissibility multipliers by Markov random fields, (5) Up scaling, (6) The link between model parameters, well observations and production history in a simple test case, (7) Sampling the posterior using optimization in a hierarchical model, (8) A comparison of Rejection Sampling and Metropolis-Hastings algorithm, (9) Stochastic simulation and conditioning by annealing in reservoir description, and (10) Uncertainty assessment in history matching and forecasting. 139 refs., 85 figs., 1 tab.

  12. Forecasting contaminant concentrations: Spills in the White Oak Creek Basin

    International Nuclear Information System (INIS)

    Borders, D.M.; Hyndman, D.W.; Huff, D.D.

    1987-01-01

    The Streamflow Synthesis and Reservoir Regulation (SSARR) model has been installed and sufficiently calibrated for use in managing accidental release of contaminants in surface waters of the White Oak Creek (WOC) watershed at ORNL. The model employs existing watershed conditions, hydrologic parameters representing basin response to precipitation, and a Quantitative Precipitation Forecast (QPF) to predict variable flow conditions throughout the basin. Natural runoff from each of the hydrologically distinct subbasins is simulated and added to specified plant and process water discharges. The resulting flows are then routed through stream reaches and eventually to White Oak Lake (WOL), which is the outlet from the WOC drainage basin. In addition, the SSARR model is being used to simulate change in storage volumes and pool levels in WOL, and most recently, routing characteristics of contaminant spills through WOC and WOL. 10 figs

  13. Requirements and benefits of flow forecasting for improving hydropower generation

    NARCIS (Netherlands)

    Dong, Xiaohua; Vrijling, J.K.; Dohmen-Janssen, Catarine M.; Ruigh, E.; Booij, Martijn J.; Stalenberg, B.; Hulscher, Suzanne J.M.H.; van Gelder, P.H.A.J.M.; Verlaan, M.; Zijderveld, A.; Waarts, P.

    2005-01-01

    This paper presents a methodology to identify the required lead time and accuracy of flow forecasting for improving hydropower generation of a reservoir, by simulating the benefits (in terms of electricity generated) obtained from the forecasting with varying lead times and accuracies. The

  14. Evaluating the Implications of Climate Phenomenon Indices in Supporting Reservoir Operation Using the Artificial Neural Network and Decision-Tree Methods: A Case Study on Trinity Lake in Northern California

    Science.gov (United States)

    Yang, T.; Akbari Asanjan, A.; Gao, X.; Sorooshian, S.

    2016-12-01

    Reservoirs are fundamental human-built infrastructures that collect, store, and deliver fresh surface water in a timely manner for all kinds of purposes, including residential and industrial water supply, flood control, hydropower, and irrigation, etc. Efficient reservoir operation requires that policy makers and operators understand how reservoir inflows, available storage, and discharges are changing under different climatic conditions. Over the last decade, the uses of Artificial Intelligence and Data Mining (AI & DM) techniques in assisting reservoir management and seasonal forecasts have been increasing. Therefore, in this study, two distinct AI & DM methods, Artificial Neural Network (ANN) and Random Forest (RF), are employed and compared with respect to their capabilities of predicting monthly reservoir inflow, managing storage, and scheduling reservoir releases. A case study on Trinity Lake in northern California is conducted using long-term (over 50 years) reservoir operation records and 17 known climate phenomenon indices, i.e. PDO and ENSO, etc., as predictors. Results show that (1) both ANN and RF are capable of providing reasonable monthly reservoir storage, inflow, and outflow prediction with satisfactory statistics, and (2) climate phenomenon indices are useful in assisting monthly or seasonal forecasts of reservoir inflow and outflow. It is also found that reservoir storage has a consistent high autocorrelation effect, while inflow and outflow are more likely to be influenced by climate conditions. Using a Gini diversity index, RF method identifies that the reservoir discharges are associated with Southern Oscillation Index (SOI) and reservoir inflows are influenced by multiple climate phenomenon indices during different seasons. Furthermore, results also show that, during the winter season, reservoir discharges are controlled by the storage level for flood-control purposes, while, during the summer season, the flood-control operation is not as

  15. A source classification framework supporting pollutant source mapping, pollutant release prediction, transport and load forecasting, and source control planning for urban environments

    DEFF Research Database (Denmark)

    Lützhøft, Hans-Christian Holten; Donner, Erica; Wickman, Tonie

    2012-01-01

    for this purpose. Methods Existing source classification systems were examined by a multidisciplinary research team, and an optimised SCF was developed. The performance and usability of the SCF were tested using a selection of 25 chemicals listed as priority pollutants in Europe. Results The SCF is structured...... in the form of a relational database and incorporates both qualitative and quantitative source classification and release data. The system supports a wide range of pollution monitoring and management applications. The SCF functioned well in the performance test, which also revealed important gaps in priority...

  16. Integrating gravimetric and interferometric synthetic aperture radar data for enhancing reservoir history matching of carbonate gas and volatile oil reservoirs

    KAUST Repository

    Katterbauer, Klemens

    2016-08-25

    Reservoir history matching is assuming a critical role in understanding reservoir characteristics, tracking water fronts, and forecasting production. While production data have been incorporated for matching reservoir production levels and estimating critical reservoir parameters, the sparse spatial nature of this dataset limits the efficiency of the history matching process. Recently, gravimetry techniques have significantly advanced to the point of providing measurement accuracy in the microgal range and consequently can be used for the tracking of gas displacement caused by water influx. While gravity measurements provide information on subsurface density changes, i.e., the composition of the reservoir, these data do only yield marginal information about temporal displacements of oil and inflowing water. We propose to complement gravimetric data with interferometric synthetic aperture radar surface deformation data to exploit the strong pressure deformation relationship for enhancing fluid flow direction forecasts. We have developed an ensemble Kalman-filter-based history matching framework for gas, gas condensate, and volatile oil reservoirs, which synergizes time-lapse gravity and interferometric synthetic aperture radar data for improved reservoir management and reservoir forecasts. Based on a dual state-parameter estimation algorithm separating the estimation of static reservoir parameters from the dynamic reservoir parameters, our numerical experiments demonstrate that history matching gravity measurements allow monitoring the density changes caused by oil-gas phase transition and water influx to determine the saturation levels, whereas the interferometric synthetic aperture radar measurements help to improve the forecasts of hydrocarbon production and water displacement directions. The reservoir estimates resulting from the dual filtering scheme are on average 20%-40% better than those from the joint estimation scheme, but require about a 30% increase in

  17. In the Way of Peacemaker Guide Curve between Water Supply and Flood Control for Short Term Reservoir Operation

    Science.gov (United States)

    Uysal, G.; Sensoy, A.; Yavuz, O.; Sorman, A. A.; Gezgin, T.

    2012-04-01

    taking inflow, elevation, precipitation and snow water equivalent into consideration to propose alternative simulations as a decision support system. After that, the releases are subjected to user-defined rules. Thus, previous year reservoir simulations are compared with observed reservoir levels and releases. Hypothetical flood scenarios are tested in case of different storm event timing and sizing. Numerical weather prediction data of Mesoscale Model 5 (MM5) can be used for temperature and precipitation forecasts that will form the inputs for a hydrological model. The estimated flows can be used for real time short term decisions for reservoir simulation based on variable guide curve and user defined rules.

  18. Communicating uncertainty in hydrological forecasts: mission impossible?

    Science.gov (United States)

    Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

    2010-05-01

    Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted

  19. Magnetogram Forecast: An All-Clear Space Weather Forecasting System

    Science.gov (United States)

    Barghouty, Nasser; Falconer, David

    2015-01-01

    Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

  20. Hydrological Analysis for Inflow Forecasting into Temengor Dam

    Science.gov (United States)

    Najid, MI; Sidek, LM; Hidayah, B.; Roseli, ZA

    2016-03-01

    These days, natural disaster such as flood is the main concern for hydrologists. One of solutions in understanding the reason of flood is by prediction of the event sooner than normal occurrence. One of the criteria is lead time or travel time that is important in the study of fresh waters and flood events. Therefore, estimation of lead or travel time for flood event can be beneficial primary information. The objective of this study is to estimate the lead time or travel time for outlet of Temengor dam in Malaysia. Tenaga Nasional Berhad (TNB) Sungai Perak dam operation has the main contribution on decision support for early water released and flood warning to authorities and locals resident for in the down streams area. For this study, hydrological analysis carried out will help to determine which years that give more rainfall contribution into the reservoir. Rainfall contribution of reservoir help to understanding rainfall distribution and peak discharge on that period. It also help for calibration of forecasting model system for better accuracy of flood hydrograph. There may be various methods to determine the rainfall contribution of catchment. The result has shown that, the rainfall contribution for Temengor catchment, is more on November in each year which is the monsoon season in Malaysia. TNB dam operational decision support systems can prepare and be more aware at this time for flood control and flood mitigation.

  1. Great landslide events in Italian artificial reservoirs

    Directory of Open Access Journals (Sweden)

    A. Panizzo

    2005-01-01

    Full Text Available The empirical formulations to forecast landslide generated water waves, recently defined in the framework of a research program funded by the Italian National Dam Office RID (Registro Italiano Dighe, are here used to study three real cases of subaerial landslides which fell down italian artificial reservoirs. It is well known that impulse water waves generated by landslides constitute a very dangerous menace for human communities living in the shoreline of the artificial basin or downstream the dam. In 1963, the menace became tragedy, when a 270 millions m3 landslide fell down the Vajont reservoir (Italy, generated an impulse wave which destroyed the city of Longarone, and killed 2000 people. The paper is aimed at presenting the very satisfactorily reproduction of the events at hand by using forecasting formulations.  

  2. Great landslide events in Italian artificial reservoirs

    Science.gov (United States)

    Panizzo, A.; de Girolamo, P.; di Risio, M.; Maistri, A.; Petaccia, A.

    2005-09-01

    The empirical formulations to forecast landslide generated water waves, recently defined in the framework of a research program funded by the Italian National Dam Office RID (Registro Italiano Dighe), are here used to study three real cases of subaerial landslides which fell down italian artificial reservoirs. It is well known that impulse water waves generated by landslides constitute a very dangerous menace for human communities living in the shoreline of the artificial basin or downstream the dam. In 1963, the menace became tragedy, when a 270 millions m3 landslide fell down the Vajont reservoir (Italy), generated an impulse wave which destroyed the city of Longarone, and killed 2000 people. The paper is aimed at presenting the very satisfactorily reproduction of the events at hand by using forecasting formulations.

  3. kosh Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  4. kpdt Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  5. kewr Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  6. kiso Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. kpga Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  8. kbkw Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. ktcl Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. pgwt Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. kpsp Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. kbih Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. kdnl Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. kart Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. kilm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. kpne Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. kabi Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. ptpn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. kblf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. panc Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. kpbi Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. kgdv Terminal Aerodrome Forecast

    Data.gov (United States)

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  13. kcre Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. klws Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. kotm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. khqm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. kabr Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. klal Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. kelp Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. kecg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. khbg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. kpbf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  3. konp Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  4. pkwa Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  5. ktvf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  6. paga Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. khks Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  8. kdsm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. kpsm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. kgrb Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. kgmu Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. papg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. kbgm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. pamc Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. klrd Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. ksan Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. patk Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. kowb Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. klru Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. kfxe Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. kjct Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. kcrg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  3. paaq Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  4. kaex Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  5. klbx Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  6. kmia Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. kpit Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  8. kcrw Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. paen Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. kast Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. kuin Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. kmht Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. kcys Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. kflo Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. pakn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. pabt Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. krdg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. khdn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. kjac Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. kphx Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. A Time Domain Update Method for Reservoir History Matching of Electromagnetic Data

    KAUST Repository

    Katterbauer, Klemens

    2014-03-25

    The oil & gas industry has been the backbone of the world\\'s economy in the last century and will continue to be in the decades to come. With increasing demand and conventional reservoirs depleting, new oil industry projects have become more complex and expensive, operating in areas that were previously considered impossible and uneconomical. Therefore, good reservoir management is key for the economical success of complex projects requiring the incorporation of reliable uncertainty estimates for reliable production forecasts and optimizing reservoir exploitation. Reservoir history matching has played here a key role incorporating production, seismic, electromagnetic and logging data for forecasting the development of reservoirs and its depletion. With the advances in the last decade, electromagnetic techniques, such as crosswell electromagnetic tomography, have enabled engineers to more precisely map the reservoirs and understand their evolution. Incorporating the large amount of data efficiently and reducing uncertainty in the forecasts has been one of the key challenges for reservoir management. Computing the conductivity distribution for the field for adjusting parameters in the forecasting process via solving the inverse problem has been a challenge, due to the strong ill-posedness of the inversion problem and the extensive manual calibration required, making it impossible to be included into an efficient reservoir history matching forecasting algorithm. In the presented research, we have developed a novel Finite Difference Time Domain (FDTD) based method for incorporating electromagnetic data directly into the reservoir simulator. Based on an extended Archie relationship, EM simulations are performed for both forecasted and Porosity-Saturation retrieved conductivity parameters being incorporated directly into an update step for the reservoir parameters. This novel direct update method has significant advantages such as that it overcomes the expensive and ill

  2. Robust forecast comparison

    OpenAIRE

    Jin, Sainan; Corradi, Valentina; Swanson, Norman

    2015-01-01

    Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of general-loss (GL) forecast superiority and convex-loss (CL) forecast superiority, and we establish a ...

  3. Forecaster Behaviour and Bias in Macroeconomic Forecasts

    OpenAIRE

    Roy Batchelor

    2007-01-01

    This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990–2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of i...

  4. Weather forecast

    CERN Document Server

    Courtier, P

    1994-02-07

    Weather prediction is performed using the numerical model of the atmosphere evolution.The evolution equations are derived from the Navier Stokes equation for the adiabatic part but the are very much complicated by the change of phase of water, the radiation porocess and the boundary layer.The technique used operationally is described. Weather prediction is an initial value problem and accurate initial conditions need to be specified. Due to the small number of observations available (105 ) as compared to the dimension of the model state variable (107),the problem is largely underdetermined. Techniques of optimal control and inverse problems are used and have been adapted to the large dimension of our problem. our problem.The at mosphere is a chaotic system; the implication for weather prediction is discussed. Ensemble prediction is used operationally and the technique for generating initial conditions which lead to a numerical divergence of the subsequent forecasts is described.

  5. Robustness of a multiple-use reservoir to seasonal runoff shifts associated with climate change

    International Nuclear Information System (INIS)

    Lettenmaier, D.P.; Brettman, K.L.

    1990-05-01

    Although much remains to be learned about long-term climate change associated with anthropogenic increases in concentrations of the so-called ''greenhouse gases,'' such as carbon dioxide and methane, there is a general consensus that some global warming will result from past and present emissions. In the western United States, the dominant hydrologic effect of such warming, aside from any accompanying changes in precipitation, would be to reduce winter snow accumulations in mountainous headwaters regions. To assess the robustness of reservoir operation to such shifts in seasonal runoff, simulations were developed of monthly runoff for the American River, Washington, using the National Weather Service River Forecast System. The American River is presently unregulated; however, we tested the performance of hypothetical reservoirs with capacity of 0.25 and 0.50 of the mean annual flow for a range of annual temperature changes from 0.0 (present climate) to 4.0 degree C. We considered a multiple-purpose reservoir system operated for water supply ad hydropower, with minimum releases required for fisheries enhancement. In addition to evaluating the sensitivity of water supply, low flow, and hydropower performance using a heuristic operating rule, the relative performance of the system under present and altered climates was evaluated using an optimization algorithm, extended linear quadratic Gaussian control. This paper reports the results of hydrologic simulations for the American River, Washington. 13 refs., 8 figs

  6. Fluvial facies reservoir productivity prediction method based on principal component analysis and artificial neural network

    Directory of Open Access Journals (Sweden)

    Pengyu Gao

    2016-03-01

    Full Text Available It is difficult to forecast the well productivity because of the complexity of vertical and horizontal developments in fluvial facies reservoir. This paper proposes a method based on Principal Component Analysis and Artificial Neural Network to predict well productivity of fluvial facies reservoir. The method summarizes the statistical reservoir factors and engineering factors that affect the well productivity, extracts information by applying the principal component analysis method and approximates arbitrary functions of the neural network to realize an accurate and efficient prediction on the fluvial facies reservoir well productivity. This method provides an effective way for forecasting the productivity of fluvial facies reservoir which is affected by multi-factors and complex mechanism. The study result shows that this method is a practical, effective, accurate and indirect productivity forecast method and is suitable for field application.

  7. Real-time data processing and inflow forecasting

    International Nuclear Information System (INIS)

    Olason, T.; Lafreniere, M.

    1998-01-01

    One of the key inputs into the short-term scheduling of hydroelectric generation is inflow forecasting which is needed for natural or unregulated inflows into various lakes, reservoirs and river sections. The forecast time step and time horizon are determined by the time step and the scheduling horizon. Acres International Ltd. has developed the Vista Decision Support System (DSS) in which the time step is one hour and the scheduling can be done up to two weeks into the future. This paper presents the basis of the operational flow-forecasting module of the Vista DSS software and its application to flow forecasting for 16 basins within Nova Scotia Power's hydroelectric system. Among the tasks performed by the software are collection and treatment of data (in real time) regarding meteorological forecasts, reviews and monitoring of hydro-meteorological data, updating of the state variables in the module, and the review and adjustment of sub-watershed forecasts

  8. Optimal Operation of Hydropower Reservoirs under Climate Change: The Case of Tekeze Reservoir, Eastern Nile

    Directory of Open Access Journals (Sweden)

    Fikru Fentaw Abera

    2018-03-01

    Full Text Available Optimal operation of reservoirs is very essential for water resource planning and management, but it is very challenging and complicated when dealing with climate change impacts. The objective of this paper was to assess existing and future hydropower operation at the Tekeze reservoir in the face of climate change. In this study, a calibrated and validated Soil and Water Assessment Tool (SWAT was used to model runoff inflow into the Tekeze hydropower reservoir under present and future climate scenarios. Inflow to the reservoir was simulated using hydro-climatic data from an ensemble of downscaled climate data based on the Coordinated Regional climate Downscaling Experiment over African domain (CORDEX-Africa with Coupled Intercomparison Project Phase 5 (CMIP5 simulations under Representative Concentration Pathway (RCP4.5 and RCP8.5 climate scenarios. Observed and projected inflows to Tekeze hydropower reservoir were used as input to the US Army Corps of Engineer’s Reservoir Evaluation System Perspective Reservoir Model (HEC-ResPRM, a reservoir operation model, to optimize hydropower reservoir release, storage and pool level. Results indicated that climate change has a clear impact on reservoir inflow and showed increase in annual and monthly inflow into the reservoir except in dry months from May to June under RCP4.5 and RCP8.5 climate scenarios. HEC-ResPRM optimal operation results showed an increase in Tekeze reservoir power storage potential up to 25% and 30% under RCP4.5 and RCP8.5 climate scenarios, respectively. This implies that Tekeze hydropower production will be affected by climate change. This analysis can be used by water resources planners and mangers to develop reservoir operation techniques considering climate change impact to increase power production.

  9. Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

    Science.gov (United States)

    Lu, M.; Lall, U.

    2013-12-01

    In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The

  10. National Forecast Charts

    Science.gov (United States)

    code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. National Forecast Charts

  11. Are Forecast Updates Progressive?

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); Ph.H.B.F. Franses (Philip Hans); M.J. McAleer (Michael)

    2010-01-01

    textabstractMacro-economic forecasts typically involve both a model component, which is replicable, as well as intuition, which is non-replicable. Intuition is expert knowledge possessed by a forecaster. If forecast updates are progressive, forecast updates should become more accurate, on average,

  12. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

    Science.gov (United States)

    Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

    2017-01-01

    Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  13. SILTATION IN RESERVOIRS

    African Journals Online (AJOL)

    Keywords: reservoir model, siltation, sediment, catchment, sediment transport. 1. Introduction. Sediment ... rendered water storage structures useless in less than 25 years. ... reservoir, thus reducing the space available for water storage and ...

  14. Reservoir fisheries of Asia

    International Nuclear Information System (INIS)

    Silva, S.S. De.

    1990-01-01

    At a workshop on reservoir fisheries research, papers were presented on the limnology of reservoirs, the changes that follow impoundment, fisheries management and modelling, and fish culture techniques. Separate abstracts have been prepared for three papers from this workshop

  15. Parâmetros de projeto de microrreservatório, de pavimentos permeáveis e de previsão de enchentes urbanas Design parameters for micro reservoir, for porous pavements and for forecast of urban flow

    Directory of Open Access Journals (Sweden)

    Lourenço Leme da Costa Junior

    2006-03-01

    Full Text Available Esta pesquisa teve como objetivo principal avaliar o uso e a ocupação dos lotes de uma área urbana e analisar as possibilidades de uso das medidas de controle local de inundação: microrreservatórios de detenção e pavimentos permeáveis. A área de estudo foi a Sub-bacia Hidrográfica Urbana da Ponte Seca (SBHUPS, em Jaboticabal - SP. O total de lotes da SBHUPS é 1.777. Avaliaram-se 164 lotes, por amostragem aleatória estratificada proporcional de acordo com a área. Utilizou-se de levantamento de campo, informações cadastrais e entrevistas com moradores para a coleta dos dados. Caracterizaram-se a área livre, área impermeabilizada, área construída, taxa de ocupação (TO, taxa de ocupação e impermeabilização (TOI, tipo de solo, nível do lençol freático e topografia de cada lote amostrado. Argüiram-se os moradores sobre a aceitação do uso das medidas. Estes parâmetros foram usados para avaliar as possibilidades de suas implantações e, então, avaliaram-se os custos. Os valores médios por estrato indicam que a TO e a TOI decrescem com o aumento da área do lote. Obtiveram-se relações entre TO e área do lote, TOI e área do lote e TO e TOI representadas por equações, cujos coeficientes de determinação ficaram acima de 0,96. O uso dos microrreservatórios de detenção, como medida de controle, foi limitado pela aceitação dos moradores, a 82,8% dos lotes. O uso do pavimento permeável foi restringido pelos parâmetros área livre e aceitação dos moradores.This report had the main objective to evaluate the use and the occupation of the plot from an urban hydrographic basin and to analyze the possibilities at the use of measures of local control of floods, such as micro reservoir of detention and porous pavements. The area studied was the urban hydrographic basin from "Ponte Seca" (SBHUPS, on Jaboticabal City, São Paulo. The total of plots on BHUPS is 1.777. During the research it was analyzed 164 plots, using

  16. Large reservoirs: Chapter 17

    Science.gov (United States)

    Miranda, Leandro E.; Bettoli, Phillip William

    2010-01-01

    Large impoundments, defined as those with surface area of 200 ha or greater, are relatively new aquatic ecosystems in the global landscape. They represent important economic and environmental resources that provide benefits such as flood control, hydropower generation, navigation, water supply, commercial and recreational fisheries, and various other recreational and esthetic values. Construction of large impoundments was initially driven by economic needs, and ecological consequences received little consideration. However, in recent decades environmental issues have come to the forefront. In the closing decades of the 20th century societal values began to shift, especially in the developed world. Society is no longer willing to accept environmental damage as an inevitable consequence of human development, and it is now recognized that continued environmental degradation is unsustainable. Consequently, construction of large reservoirs has virtually stopped in North America. Nevertheless, in other parts of the world construction of large reservoirs continues. The emergence of systematic reservoir management in the early 20th century was guided by concepts developed for natural lakes (Miranda 1996). However, we now recognize that reservoirs are different and that reservoirs are not independent aquatic systems inasmuch as they are connected to upstream rivers and streams, the downstream river, other reservoirs in the basin, and the watershed. Reservoir systems exhibit longitudinal patterns both within and among reservoirs. Reservoirs are typically arranged sequentially as elements of an interacting network, filter water collected throughout their watersheds, and form a mosaic of predictable patterns. Traditional approaches to fisheries management such as stocking, regulating harvest, and in-lake habitat management do not always produce desired effects in reservoirs. As a result, managers may expend resources with little benefit to either fish or fishing. Some locally

  17. Forecasting freight flows

    DEFF Research Database (Denmark)

    Lyk-Jensen, Stéphanie

    2011-01-01

    Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...... constitute a valuable input to freight models for forecasting future capacity problems.......Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...

  18. Gambling scores for earthquake predictions and forecasts

    Science.gov (United States)

    Zhuang, Jiancang

    2010-04-01

    This paper presents a new method, namely the gambling score, for scoring the performance earthquake forecasts or predictions. Unlike most other scoring procedures that require a regular scheme of forecast and treat each earthquake equally, regardless their magnitude, this new scoring method compensates the risk that the forecaster has taken. Starting with a certain number of reputation points, once a forecaster makes a prediction or forecast, he is assumed to have betted some points of his reputation. The reference model, which plays the role of the house, determines how many reputation points the forecaster can gain if he succeeds, according to a fair rule, and also takes away the reputation points betted by the forecaster if he loses. This method is also extended to the continuous case of point process models, where the reputation points betted by the forecaster become a continuous mass on the space-time-magnitude range of interest. We also calculate the upper bound of the gambling score when the true model is a renewal process, the stress release model or the ETAS model and when the reference model is the Poisson model.

  19. Mrica Reservoir Sedimentation: Current Situation and Future Necessary Management

    Directory of Open Access Journals (Sweden)

    Puji Utomo

    2017-09-01

    Full Text Available Mrica Reservoir is one of many reservoirs located in Central Java that experienced a considerably high sedimentation during the last ten years. This condition has caused a rapid decrease in reservoir capacity. Various countermeasures have been introduced to reduce the rate of the reservoir sedimentation through catchment management and reservoir operation by means of flushing and/or dredging. However, the sedimentation remains intensive so that the fulfillment of water demand for electrical power generation was seriously affected. This paper presents the results of evaluation on the dynamics of the purpose of this research is to evaluate the sediment balance of the Mrica Reservoir based on two different scenarios, i.e. the existing condition and another certain type of reservoir management. The study on sediment balance was carried out by estimating the sediment inflow applying sheet erosion method in combination with the analysis of sediment rating curve. The measurement of the deposited sediment rate in the reservoir was conducted through the periodic echo sounding, whereas identification of the number of sediment that has been released from the reservoir was carried out through the observation on both flushing and dredging activities. The results show that during the last decade, the rate of the sediment inflow was approximately 5.869 MCM/year, whereas the released sediment from the reservoir was 4.097 MCM/year. In order to maintain the reservoir capacity, therefore, at least 1.772 MCM/year should be released from the reservoir by means of either flushing or dredging. Sedimentation management may prolong the reservoir’s service life to exceed the design life. Without sediment management, the lifetime of the reservoir would have finished by 2016, whereas with the proper management the lifetime may be extended to 2025.

  20. Design and development of bio-inspired framework for reservoir operation optimization

    Science.gov (United States)

    Asvini, M. Sakthi; Amudha, T.

    2017-12-01

    Frameworks for optimal reservoir operation play an important role in the management of water resources and delivery of economic benefits. Effective utilization and conservation of water from reservoirs helps to manage water deficit periods. The main challenge in reservoir optimization is to design operating rules that can be used to inform real-time decisions on reservoir release. We develop a bio-inspired framework for the optimization of reservoir release to satisfy the diverse needs of various stakeholders. In this work, single-objective optimization and multiobjective optimization problems are formulated using an algorithm known as "strawberry optimization" and tested with actual reservoir data. Results indicate that well planned reservoir operations lead to efficient deployment of the reservoir water with the help of optimal release patterns.

  1. Reservoir Operating Rule Optimization for California's Sacramento Valley

    Directory of Open Access Journals (Sweden)

    Timothy Nelson

    2016-03-01

    Full Text Available doi: http://dx.doi.org/10.15447/sfews.2016v14iss1art6Reservoir operating rules for water resource systems are typically developed by combining intuition, professional discussion, and simulation modeling. This paper describes a joint optimization–simulation approach to develop preliminary economically-based operating rules for major reservoirs in California’s Sacramento Valley, based on optimized results from CALVIN, a hydro-economic optimization model. We infer strategic operating rules from the optimization model results, including storage allocation rules to balance storage among multiple reservoirs, and reservoir release rules to determine monthly release for individual reservoirs. Results show the potential utility of considering previous year type on water availability and various system and sub-system storage conditions, in addition to normal consideration of local reservoir storage, season, and current inflows. We create a simple simulation to further refine and test the derived operating rules. Optimization model results show particular insights for balancing the allocation of water storage among Shasta, Trinity, and Oroville reservoirs over drawdown and refill seasons, as well as some insights for release rules at major reservoirs in the Sacramento Valley. We also discuss the applicability and limitations of developing reservoir operation rules from optimization model results.

  2. Flood forecasting and uncertainty of precipitation forecasts

    International Nuclear Information System (INIS)

    Kobold, Mira; Suselj, Kay

    2004-01-01

    The timely and accurate flood forecasting is essential for the reliable flood warning. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual rainfall - runoff models enable the estimation of these parameters and lead to useful operational forecasts. The accurate rainfall is the most important input into hydrological models. The input for the rainfall can be real time rain-gauges data, or weather radar data, or meteorological forecasted precipitation. The torrential nature of streams and fast runoff are characteristic for the most of the Slovenian rivers. Extensive damage is caused almost every year- by rainstorms affecting different regions of Slovenia' The lag time between rainfall and runoff is very short for Slovenian territory and on-line data are used only for now casting. Forecasted precipitations are necessary for hydrological forecast for some days ahead. ECMWF (European Centre for Medium-Range Weather Forecasts) gives general forecast for several days ahead while more detailed precipitation data with limited area ALADIN/Sl model are available for two days ahead. There is a certain degree of uncertainty using such precipitation forecasts based on meteorological models. The variability of precipitation is very high in Slovenia and the uncertainty of ECMWF predicted precipitation is very large for Slovenian territory. ECMWF model can predict precipitation events correctly, but underestimates amount of precipitation in general The average underestimation is about 60% for Slovenian region. The predictions of limited area ALADIN/Si model up to; 48 hours ahead show greater applicability in hydrological forecasting. The hydrological models are sensitive to precipitation input. The deviation of runoff is much bigger than the rainfall deviation. Runoff to rainfall error fraction is about 1.6. If spatial and time distribution

  3. a system approach to the long term forecasting of the climat data in baikal region

    Science.gov (United States)

    Abasov, N.; Berezhnykh, T.

    2003-04-01

    that take place in the Baikal, the Bratsk and Ust-Ilimsk reservoirs: long low-water periods and sudden periods of extremely high water levels. For example, low-water periods, observed in the reservoirs of the Angara cascade can be classified under four risk categories : 1 - acceptable (negligible reduction of electric power generation by hydropower plants; certain difficulty in meeting environmental and navigation requirements); 2 - significant (substantial reduction of electric power generation by hydropower plants; certain restriction on water releases for navigation; violation of environmental requirements in some years); 3 - emergency (big losses in electric power generation; limited electricity supply to large consumers; significant restriction of water releases for navigation; threat of exposure of drinkable water intake works; violation of environmental requirements for a number of years); 4 - catastrophic (energy crisis; social crisis exposure of drinkable water intake works; termination of navigation; environmental catastrophe). Management of energy systems consists in operative, many-year regulation and perspective planning and has to take into account the analysis of operative data (water reserves in reservoirs), long-term statistics and relations among natural processes and also forecasts - short-term (for a day, week, decade), long-term and/or super-long-term (from a month to several decades). Such natural processes as water inflow to reservoirs, air temperatures during heating periods depend in turn on external factors: prevailing types of atmospheric circulation, intensity of the 11- and 22-year cycles of solar activity, volcanic activity, interaction between the ocean and atmosphere, etc. Until recently despite the formed scientific schools on long-term forecasting (I.P.Druzhinin, A.P.Reznikhov) the energy system management has been based on specially drawn dispatching schedules and long-term hydrometeorological forecasts only without attraction of

  4. ENSEMBLE methods to reconcile disparate national long range dispersion forecasts

    OpenAIRE

    Mikkelsen, Torben; Galmarini, S.; Bianconi, R.; French, S.

    2003-01-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparatenational forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an a...

  5. Formation and forecast of the daily price of the electric power in the chain Nare-Guatape-San Carlos

    International Nuclear Information System (INIS)

    Romero, Alejandro; Carvajal, Luis

    2003-01-01

    This work shows three different methodologies for the understanding and forecast of the electric energy prices in the chain Nare - Guatape - San Carlos: lineal multivariate model, autoregressive deterministic model and Fourier series decomposition. The electric energy price depends basically of the reservoir level and river flow, not only its own but the reservoir down and up, waters. About prices forecast, they can be modeled with an autoregressive process. Prices forecast follows the tendency and captures with acceptable precision the maximum prices due especially to the low hydrology and price variability for daily and weekly regulation reservoirs

  6. Fuel cycle forecasting - there are forecasts and there are forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Puechl, K H

    1975-12-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis.

  7. Fuel cycle forecasting - there are forecasts and there are forecasts

    International Nuclear Information System (INIS)

    Puechl, K.H.

    1975-01-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis. (author)

  8. Fortescue reservoir development and reservoir studies

    Energy Technology Data Exchange (ETDEWEB)

    Henzell, S.T.; Hicks, G.J.; Horden, M.J.; Irrgang, H.R.; Janssen, E.J.; Kable, C.W.; Mitchell, R.A.H.; Morrell, N.W.; Palmer, I.D.; Seage, N.W.

    1985-03-01

    The Fortescue field in the Gippsland Basin, offshore southeastern Australia is being developed from two platforms (Fortescue A and Cobia A) by Esso Australia Ltd. (operator) and BHP Petroleum. The Fortescue reservoir is a stratigraphic trap at the top of the Latrobe Group of sediments. It overlies the western flank of the Halibut and Cobia fields and is separated from them by a non-net sequence of shales and coals which form a hydraulic barrier between the two systems. Development drilling into the Fortescue reservoir commenced in April 1983 with production coming onstream in May 1983. Fortescue, with booked reserves of 44 stock tank gigalitres (280 million stock tank barrels) of 43/sup 0/ API oil, is the seventh major oil reservoir to be developed in the offshore Gippsland Basin by Esso/BHP. In mid-1984, after drilling a total of 20 exploration and development wells, and after approximately one year of production, a detailed three-dimensional, two-phase reservoir simulation study was performed to examine the recovery efficiency, drainage patterns, pressure performance and production rate potential of the reservoir. The model was validated by history matching an extensive suite of Repeat Formation Test (RFT) pressure data. The results confirmed the reserves basis, and demonstrated that the ultimate oil recovery from the reservoir is not sensitive to production rate. This result is consistent with studies on other high quality Latrobe Group reservoirs in the Gippsland Basin which contain undersaturated crudes and receive very strong water drive from the Basin-wide aquifer system. With the development of the simulation model during the development phase, it has been possible to more accurately define the optimal well pattern for the remainder of the development.

  9. Forecasting production in Liquid Rich Shale plays

    Science.gov (United States)

    Nikfarman, Hanieh

    Production from Liquid Rich Shale (LRS) reservoirs is taking center stage in the exploration and production of unconventional reservoirs. Production from the low and ultra-low permeability LRS plays is possible only through multi-fractured horizontal wells (MFHW's). There is no existing workflow that is applicable to forecasting multi-phase production from MFHW's in LRS plays. This project presents a practical and rigorous workflow for forecasting multiphase production from MFHW's in LRS reservoirs. There has been much effort in developing workflows and methodology for forecasting in tight/shale plays in recent years. The existing workflows, however, are applicable only to single phase flow, and are primarily used in shale gas plays. These methodologies do not apply to the multi-phase flow that is inevitable in LRS plays. To account for complexities of multiphase flow in MFHW's the only available technique is dynamic modeling in compositional numerical simulators. These are time consuming and not practical when it comes to forecasting production and estimating reserves for a large number of producers. A workflow was developed, and validated by compositional numerical simulation. The workflow honors physics of flow, and is sufficiently accurate while practical so that an analyst can readily apply it to forecast production and estimate reserves in a large number of producers in a short period of time. To simplify the complex multiphase flow in MFHW, the workflow divides production periods into an initial period where large production and pressure declines are expected, and the subsequent period where production decline may converge into a common trend for a number of producers across an area of interest in the field. Initial period assumes the production is dominated by single-phase flow of oil and uses the tri-linear flow model of Erdal Ozkan to estimate the production history. Commercial software readily available can simulate flow and forecast production in this

  10. Robust Approaches to Forecasting

    OpenAIRE

    Jennifer Castle; David Hendry; Michael P. Clements

    2014-01-01

    We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods ar...

  11. Inflation Forecast Contracts

    OpenAIRE

    Gersbach, Hans; Hahn, Volker

    2012-01-01

    We introduce a new type of incentive contract for central bankers: inflation forecast contracts, which make central bankers’ remunerations contingent on the precision of their inflation forecasts. We show that such contracts enable central bankers to influence inflation expectations more effectively, thus facilitating more successful stabilization of current inflation. Inflation forecast contracts improve the accuracy of inflation forecasts, but have adverse consequences for output. On balanc...

  12. Transport of reservoir fines

    DEFF Research Database (Denmark)

    Yuan, Hao; Shapiro, Alexander; Stenby, Erling Halfdan

    Modeling transport of reservoir fines is of great importance for evaluating the damage of production wells and infectivity decline. The conventional methodology accounts for neither the formation heterogeneity around the wells nor the reservoir fines’ heterogeneity. We have developed an integral...... dispersion equation in modeling the transport and the deposition of reservoir fines. It successfully predicts the unsymmetrical concentration profiles and the hyperexponential deposition in experiments....

  13. Sirocco - Fukushima Forecast Description

    International Nuclear Information System (INIS)

    2011-01-01

    SYMPHONIE-NH is the non-hydrostatic ocean model following the Boussinesq hydrostatic SYMPHONIE-2010 model developed by the Sirocco system team (CNRS and Toulouse University). Both are using an Arakawa type finite difference method for the C grid. The R and D team generally gives priority to a physically based approach of modelling (global conservation of the mechanical energy, consistency of pressure and density, accuracy of the bottom pressure torque,...) that tends to favour low order and robust numerical schemes. Most of the physical and numerical options (Non-Hydrostatic, free surface, generalised coordinates combined to an ALE method,...) are particularly suitable for the coastal area. At the request of the International Atomic Energy Agency (IAEA, March 14, 2011), SIROCCO is delivering every day a real time 6-day forecast bulletin of the dispersion in seawater of radionuclides emitted by the Fukushima nuclear plant. The simulations are based on the S2010.18 release of the 3D SIROCCO ocean circulation model. The system is operational since March 24 and the bulletin is available on an 'open-access' basis since March 28. The model uses a stretched horizontal grid with a variable horizontal resolution: from 600 m x 600 m at the nearest grid point from Fukushima, to 5 km x 5 km offshore. The initial fields (T, S, U, V, SSH) and the lateral open boundary conditions are provided by the Mercator PSY4V1R3 system (one field per day, horizontal resolution 1/12 deg. x 1/12 deg.). At the sea surface, the ocean model is forced by the meteorological fluxes delivered every 3 hours by ECMWF.i The tidal forcing at the lateral open boundaries is provided by the T-UGO model, implemented for this purpose by the SIROCCO team on the Japanese Pacific coast. Some details are given on the methodology: Bathymetry, Initialization and large scale forcing, Tides, Atmospheric forcing, Forecast protocol, and Scenario for radioactive tracers

  14. Sirocco - Fukushima Forecast Description

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2011-04-10

    SYMPHONIE-NH is the non-hydrostatic ocean model following the Boussinesq hydrostatic SYMPHONIE-2010 model developed by the Sirocco system team (CNRS and Toulouse University). Both are using an Arakawa type finite difference method for the C grid. The R and D team generally gives priority to a physically based approach of modelling (global conservation of the mechanical energy, consistency of pressure and density, accuracy of the bottom pressure torque,...) that tends to favour low order and robust numerical schemes. Most of the physical and numerical options (Non-Hydrostatic, free surface, generalised coordinates combined to an ALE method,...) are particularly suitable for the coastal area. At the request of the International Atomic Energy Agency (IAEA, March 14, 2011), SIROCCO is delivering every day a real time 6-day forecast bulletin of the dispersion in seawater of radionuclides emitted by the Fukushima nuclear plant. The simulations are based on the S2010.18 release of the 3D SIROCCO ocean circulation model. The system is operational since March 24 and the bulletin is available on an 'open-access' basis since March 28. The model uses a stretched horizontal grid with a variable horizontal resolution: from 600 m x 600 m at the nearest grid point from Fukushima, to 5 km x 5 km offshore. The initial fields (T, S, U, V, SSH) and the lateral open boundary conditions are provided by the Mercator PSY4V1R3 system (one field per day, horizontal resolution 1/12 deg. x 1/12 deg.). At the sea surface, the ocean model is forced by the meteorological fluxes delivered every 3 hours by ECMWF.i The tidal forcing at the lateral open boundaries is provided by the T-UGO model, implemented for this purpose by the SIROCCO team on the Japanese Pacific coast. Some details are given on the methodology: Bathymetry, Initialization and large scale forcing, Tides, Atmospheric forcing, Forecast protocol, and Scenario for radioactive tracers

  15. Gas deliverability forecasting - why bother?

    International Nuclear Information System (INIS)

    Trick, M.

    1996-01-01

    According to the author the answer to the question is an unequivocal 'yes' because gas production forecasting is extremely useful for the management and development of a gas field. To model a gas field, one must take into account reservoir performance, sandface inflow performance, wellbore pressure losses, gathering system pressure losses, and field facility performance. The integration of all these factors in a single computer-based model that incorporates proven technology will facilitate the evaluation of various development strategies. A good computer model can help to predict the most cost effective improvement methods, determine economic viability, estimate how much gas is available, evaluate whether drilling wells or adding compression will produce the most reserves, determine optimum placement of compression, evaluate changes to the gathering system, and determine if production from existing wells can be increased by wellbore modifications

  16. Fuzzy rule-based model for hydropower reservoirs operation

    Energy Technology Data Exchange (ETDEWEB)

    Moeini, R.; Afshar, A.; Afshar, M.H. [School of Civil Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)

    2011-02-15

    Real-time hydropower reservoir operation is a continuous decision-making process of determining the water level of a reservoir or the volume of water released from it. The hydropower operation is usually based on operating policies and rules defined and decided upon in strategic planning. This paper presents a fuzzy rule-based model for the operation of hydropower reservoirs. The proposed fuzzy rule-based model presents a set of suitable operating rules for release from the reservoir based on ideal or target storage levels. The model operates on an 'if-then' principle, in which the 'if' is a vector of fuzzy premises and the 'then' is a vector of fuzzy consequences. In this paper, reservoir storage, inflow, and period are used as premises and the release as the consequence. The steps involved in the development of the model include, construction of membership functions for the inflow, storage and the release, formulation of fuzzy rules, implication, aggregation and defuzzification. The required knowledge bases for the formulation of the fuzzy rules is obtained form a stochastic dynamic programming (SDP) model with a steady state policy. The proposed model is applied to the hydropower operation of ''Dez'' reservoir in Iran and the results are presented and compared with those of the SDP model. The results indicate the ability of the method to solve hydropower reservoir operation problems. (author)

  17. Flood risk management for large reservoirs

    International Nuclear Information System (INIS)

    Poupart, M.

    2006-01-01

    Floods are a major risk for dams: uncontrolled reservoir water level may cause dam overtopping, and then its failure, particularly for fill dams. Poor control of spillway discharges must be taken into consideration too, as it can increase the flood consequences downstream. In both cases, consequences on the public or on properties may be significant. Spillway design to withstand extreme floods is one response to these risks, but must be complemented by strict operating rules: hydrological forecasting, surveillance and periodic equipment controls, operating guides and the training of operators are mandatory too, in order to guarantee safe operations. (author)

  18. Electricity demand forecasting techniques

    International Nuclear Information System (INIS)

    Gnanalingam, K.

    1994-01-01

    Electricity demand forecasting plays an important role in power generation. The two areas of data that have to be forecasted in a power system are peak demand which determines the capacity (MW) of the plant required and annual energy demand (GWH). Methods used in electricity demand forecasting include time trend analysis and econometric methods. In forecasting, identification of manpower demand, identification of key planning factors, decision on planning horizon, differentiation between prediction and projection (i.e. development of different scenarios) and choosing from different forecasting techniques are important

  19. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Containing 12 new chapters, this second edition contains offers increased-coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of demand.

  20. Modelling of Reservoir Operations using Fuzzy Logic and ANNs

    Science.gov (United States)

    Van De Giesen, N.; Coerver, B.; Rutten, M.

    2015-12-01

    Today, almost 40.000 large reservoirs, containing approximately 6.000 km3 of water and inundating an area of almost 400.000 km2, can be found on earth. Since these reservoirs have a storage capacity of almost one-sixth of the global annual river discharge they have a large impact on the timing, volume and peaks of river discharges. Global Hydrological Models (GHM) are thus significantly influenced by these anthropogenic changes in river flows. We developed a parametrically parsimonious method to extract operational rules based on historical reservoir storage and inflow time-series. Managing a reservoir is an imprecise and vague undertaking. Operators always face uncertainties about inflows, evaporation, seepage losses and various water demands to be met. They often base their decisions on experience and on available information, like reservoir storage and the previous periods inflow. We modeled this decision-making process through a combination of fuzzy logic and artificial neural networks in an Adaptive-Network-based Fuzzy Inference System (ANFIS). In a sensitivity analysis, we compared results for reservoirs in Vietnam, Central Asia and the USA. ANFIS can indeed capture reservoirs operations adequately when fed with a historical monthly time-series of inflows and storage. It was shown that using ANFIS, operational rules of existing reservoirs can be derived without much prior knowledge about the reservoirs. Their validity was tested by comparing actual and simulated releases with each other. For the eleven reservoirs modelled, the normalised outflow, , was predicted with a MSE of 0.002 to 0.044. The rules can be incorporated into GHMs. After a network for a specific reservoir has been trained, the inflow calculated by the hydrological model can be combined with the release and initial storage to calculate the storage for the next time-step using a mass balance. Subsequently, the release can be predicted one time-step ahead using the inflow and storage.

  1. Reservoir Engineering Management Program

    Energy Technology Data Exchange (ETDEWEB)

    Howard, J.H.; Schwarz, W.J.

    1977-12-14

    The Reservoir Engineering Management Program being conducted at Lawrence Berkeley Laboratory includes two major tasks: 1) the continuation of support to geothermal reservoir engineering related work, started under the NSF-RANN program and transferred to ERDA at the time of its formation; 2) the development and subsequent implementation of a broad plan for support of research in topics related to the exploitation of geothermal reservoirs. This plan is now known as the GREMP plan. Both the NSF-RANN legacies and GREMP are in direct support of the DOE/DGE mission in general and the goals of the Resource and Technology/Resource Exploitation and Assessment Branch in particular. These goals are to determine the magnitude and distribution of geothermal resources and reduce risk in their exploitation through improved understanding of generically different reservoir types. These goals are to be accomplished by: 1) the creation of a large data base about geothermal reservoirs, 2) improved tools and methods for gathering data on geothermal reservoirs, and 3) modeling of reservoirs and utilization options. The NSF legacies are more research and training oriented, and the GREMP is geared primarily to the practical development of the geothermal reservoirs. 2 tabs., 3 figs.

  2. Forecasting world natural gas supply

    International Nuclear Information System (INIS)

    Al-Fattah, S. M.; Startzman, R. A.

    2000-01-01

    Using the multi-cyclic Hubert approach, a 53 country-specific gas supply model was developed which enables production forecasts for virtually all of the world's gas. Supply models for some organizations such as OPEC, non-OPEC and OECD were also developed and analyzed. Results of the modeling study indicate that the world's supply of natural gas will peak in 2014, followed by an annual decline at the rate of one per cent per year. North American gas production is reported to be currently at its peak with 29 Tcf/yr; Western Europe will reach its peak supply in 2002 with 12 Tcf. According to this forecast the main sources of natural gas supply in the future will be the countries of the former Soviet Union and the Middle East. Between them, they possess about 62 per cent of the world's ultimate recoverable natural gas (4,880 Tcf). It should be noted that these estimates do not include unconventional gas resulting from tight gas reservoirs, coalbed methane, gas shales and gas hydrates. These unconventional sources will undoubtedly play an important role in the gas supply in countries such as the United States and Canada. 18 refs., 2 tabs., 18 figs

  3. a Stochastic Approach to Multiobjective Optimization of Large-Scale Water Reservoir Networks

    Science.gov (United States)

    Bottacin-Busolin, A.; Worman, A. L.

    2013-12-01

    A main challenge for the planning and management of water resources is the development of multiobjective strategies for operation of large-scale water reservoir networks. The optimal sequence of water releases from multiple reservoirs depends on the stochastic variability of correlated hydrologic inflows and on various processes that affect water demand and energy prices. Although several methods have been suggested, large-scale optimization problems arising in water resources management are still plagued by the high dimensional state space and by the stochastic nature of the hydrologic inflows. In this work, the optimization of reservoir operation is approached using approximate dynamic programming (ADP) with policy iteration and function approximators. The method is based on an off-line learning process in which operating policies are evaluated for a number of stochastic inflow scenarios, and the resulting value functions are used to design new, improved policies until convergence is attained. A case study is presented of a multi-reservoir system in the Dalälven River, Sweden, which includes 13 interconnected reservoirs and 36 power stations. Depending on the late spring and summer peak discharges, the lowlands adjacent to Dalälven can often be flooded during the summer period, and the presence of stagnating floodwater during the hottest months of the year is the cause of a large proliferation of mosquitos, which is a major problem for the people living in the surroundings. Chemical pesticides are currently being used as a preventive countermeasure, which do not provide an effective solution to the problem and have adverse environmental impacts. In this study, ADP was used to analyze the feasibility of alternative operating policies for reducing the flood risk at a reasonable economic cost for the hydropower companies. To this end, mid-term operating policies were derived by combining flood risk reduction with hydropower production objectives. The performance

  4. Induced seismicity in geothermal reservoirs : A review of forecasting approaches

    NARCIS (Netherlands)

    Gaucher, Emmanuel; Schoenball, Martin; Heidbach, Oliver; Zang, Arno; Fokker, Peter A.; Van Wees, Jan Diederik; Kohl, Thomas

    2015-01-01

    In order to reach Europes 2020 and 2050 targets in terms of greenhouse gas emissions, geothermal resources will have to contribute substantially to meeting carbon-free energy needs. However, public opinion may prevent future large-scale application of deep geothermal power plants, because induced

  5. Monthly reservoir inflow forecasting using a new hybrid SARIMA ...

    Indian Academy of Sciences (India)

    SARIMA models are linear and do not consider the random component of statistical data. To overcome this ... lake levels using artificial intelligence models and found that, compared with other models such as. ANN, GEP has .... that should be evaluated before modelling, and if they exist, they should be removed. The com-.

  6. Induced seismicity in geothermal reservoirs: A review of forecasting approaches

    NARCIS (Netherlands)

    Gaucher, E.; Schoenball, M.; Heidbach, O.; Zang, A.; Fokker, P.A.; Wees, J.D. van; Kohl, T.

    2015-01-01

    In order to reach Europes 2020 and 2050 targets in terms of greenhouse gas emissions, geothermal resources will have to contribute substantially to meeting carbon-free energy needs. However, public opinion may prevent future large-scale application of deep geothermal power plants, because induced

  7. Simulation of Reservoir Sediment Flushing of the Three Gorges Reservoir Using an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Xueying Li

    2016-05-01

    Full Text Available Reservoir sedimentation and its effect on the environment are the most serious world-wide problems in water resources development and utilization today. As one of the largest water conservancy projects, the Three Gorges Reservoir (TGR has been controversial since its demonstration period, and sedimentation is the major concern. Due to the complex physical mechanisms of water and sediment transport, this study adopts the Error Back Propagation Training Artificial Neural Network (BP-ANN to analyze the relationship between the sediment flushing efficiency of the TGR and its influencing factors. The factors are determined by the analysis on 1D unsteady flow and sediment mathematical model, mainly including reservoir inflow, incoming sediment concentration, reservoir water level, and reservoir release. Considering the distinguishing features of reservoir sediment delivery in different seasons, the monthly average data from 2003, when the TGR was put into operation, to 2011 are used to train, validate, and test the BP-ANN model. The results indicate that, although the sample space is quite limited, the whole sediment delivery process can be schematized by the established BP-ANN model, which can be used to help sediment flushing and thus decrease the reservoir sedimentation.

  8. A framework for improving a seasonal hydrological forecasting system using sensitivity analysis

    Science.gov (United States)

    Arnal, Louise; Pappenberger, Florian; Smith, Paul; Cloke, Hannah

    2017-04-01

    Seasonal streamflow forecasts are of great value for the socio-economic sector, for applications such as navigation, flood and drought mitigation and reservoir management for hydropower generation and water allocation to agriculture and drinking water. However, as we speak, the performance of dynamical seasonal hydrological forecasting systems (systems based on running seasonal meteorological forecasts through a hydrological model to produce seasonal hydrological forecasts) is still limited in space and time. In this context, the ESP (Ensemble Streamflow Prediction) remains an attractive forecasting method for seasonal streamflow forecasting as it relies on forcing a hydrological model (starting from the latest observed or simulated initial hydrological conditions) with historical meteorological observations. This makes it cheaper to run than a standard dynamical seasonal hydrological forecasting system, for which the seasonal meteorological forecasts will first have to be produced, while still producing skilful forecasts. There is thus the need to focus resources and time towards improvements in dynamical seasonal hydrological forecasting systems which will eventually lead to significant improvements in the skill of the streamflow forecasts generated. Sensitivity analyses are a powerful tool that can be used to disentangle the relative contributions of the two main sources of errors in seasonal streamflow forecasts, namely the initial hydrological conditions (IHC; e.g., soil moisture, snow cover, initial streamflow, among others) and the meteorological forcing (MF; i.e., seasonal meteorological forecasts of precipitation and temperature, input to the hydrological model). Sensitivity analyses are however most useful if they inform and change current operational practices. To this end, we propose a method to improve the design of a seasonal hydrological forecasting system. This method is based on sensitivity analyses, informing the forecasters as to which element of

  9. Techniques for Reaeration of Hydropower Releases.

    Science.gov (United States)

    1983-02-01

    release improvement. However, selected reservoir aeration studies not conducted primarily for improving hydroturbine releases but which have application...for hydroturbine release reaeration were also reviewed. Because oxygen transfer mechanisms are vitally important to the development of more efficient...the key words turbine aeration, turbine vent, turbine I’ aspiration, hydroturbine aeration, tailrace aeration, draft tube vent, and vacuum breaker. A

  10. Adaptive Regulation of the Northern California Reservoir System for Water, Energy, and Environmental Management

    Science.gov (United States)

    Georgakakos, A. P.; Kistenmacher, M.; Yao, H.; Georgakakos, K. P.

    2014-12-01

    The 2014 National Climate Assessment of the US Global Change Research Program emphasizes that water resources managers and planners in most US regions will have to cope with new risks, vulnerabilities, and opportunities, and recommends the development of adaptive capacity to effectively respond to the new water resources planning and management challenges. In the face of these challenges, adaptive reservoir regulation is becoming all the more ncessary. Water resources management in Northern California relies on the coordinated operation of several multi-objective reservoirs on the Trinity, Sacramento, American, Feather, and San Joaquin Rivers. To be effective, reservoir regulation must be able to (a) account for forecast uncertainty; (b) assess changing tradeoffs among water uses and regions; and (c) adjust management policies as conditions change; and (d) evaluate the socio-economic and environmental benefits and risks of forecasts and policies for each region and for the system as a whole. The Integrated Forecast and Reservoir Management (INFORM) prototype demonstration project operated in Northern California through the collaboration of several forecast and management agencies has shown that decision support systems (DSS) with these attributes add value to stakeholder decision processes compared to current, less flexible management practices. Key features of the INFORM DSS include: (a) dynamically downscaled operational forecasts and climate projections that maintain the spatio-temporal coherence of the downscaled land surface forcing fields within synoptic scales; (b) use of ensemble forecast methodologies for reservoir inflows; (c) assessment of relevant tradeoffs among water uses on regional and local scales; (d) development and evaluation of dynamic reservoir policies with explicit consideration of hydro-climatic forecast uncertainties; and (e) focus on stakeholder information needs.This article discusses the INFORM integrated design concept, underlying

  11. Restoring Natural Streamflow Variability by Modifying Multi-purpose Reservoir Operation

    Science.gov (United States)

    Shiau, J.

    2010-12-01

    Multi-purpose reservoirs typically provide benefits of water supply, hydroelectric power, and flood mitigation. Hydroelectric power generations generally do not consume water. However, temporal distribution of downstream flows is highly changed due to hydro-peaking effects. Associated with offstream diversion of water supplies for municipal, industrial, and agricultural requirements, natural streamflow characteristics of magnitude, duration, frequency, timing, and rate of change is significantly altered by multi-purpose reservoir operation. Natural flow regime has long been recognized a master factor for ecosystem health and biodiversity. Restoration of altered flow regime caused by multi-purpose reservoir operation is the main objective of this study. This study presents an optimization framework that modifying reservoir operation to seeking balance between human and environmental needs. The methodology presented in this study is applied to the Feitsui Reservoir, located in northern Taiwan, with main purpose of providing stable water-supply and auxiliary purpose of electricity generation and flood-peak attenuation. Reservoir releases are dominated by two decision variables, i.e., duration of water releases for each day and percentage of daily required releases within the duration. The current releasing policy of the Feitsui Reservoir releases water for water-supply and hydropower purposes during 8:00 am to 16:00 pm each day and no environmental flows releases. Although greater power generation is obtained by 100% releases distributed within 8-hour period, severe temporal alteration of streamflow is observed downstream of the reservoir. Modifying reservoir operation by relaxing these two variables and reserve certain ratio of streamflow as environmental flow to maintain downstream natural variability. The optimal reservoir releasing policy is searched by the multi-criterion decision making technique for considering reservoir performance in terms of shortage ratio

  12. Sediment management for reservoir

    International Nuclear Information System (INIS)

    Rahman, A.

    2005-01-01

    All natural lakes and reservoirs whether on rivers, tributaries or off channel storages are doomed to be sited up. Pakistan has two major reservoirs of Tarbela and Managla and shallow lake created by Chashma Barrage. Tarbela and Mangla Lakes are losing their capacities ever since first impounding, Tarbela since 1974 and Mangla since 1967. Tarbela Reservoir receives average annual flow of about 62 MAF and sediment deposits of 0.11 MAF whereas Mangla gets about 23 MAF of average annual flows and is losing its storage at the rate of average 34,000 MAF annually. The loss of storage is a great concern and studies for Tarbela were carried out by TAMS and Wallingford to sustain its capacity whereas no study has been done for Mangla as yet except as part of study for Raised Mangla, which is only desk work. Delta of Tarbala reservoir has advanced to about 6.59 miles (Pivot Point) from power intakes. In case of liquefaction of delta by tremor as low as 0.12g peak ground acceleration the power tunnels I, 2 and 3 will be blocked. Minimum Pool of reservoir is being raised so as to check the advance of delta. Mangla delta will follow the trend of Tarbela. Tarbela has vast amount of data as reservoir is surveyed every year, whereas Mangla Reservoir survey was done at five-year interval, which has now been proposed .to be reduced to three-year interval. In addition suspended sediment sampling of inflow streams is being done by Surface Water Hydrology Project of WAPDA as also some bed load sampling. The problem of Chasma Reservoir has also been highlighted, as it is being indiscriminately being filled up and drawdown several times a year without regard to its reaction to this treatment. The Sediment Management of these reservoirs is essential and the paper discusses pros and cons of various alternatives. (author)

  13. Optimising reservoir operation

    DEFF Research Database (Denmark)

    Ngo, Long le

    Anvendelse af optimeringsteknik til drift af reservoirer er blevet et væsentligt element i vandressource-planlægning og -forvaltning. Traditionelt har reservoirer været styret af heuristiske procedurer for udtag af vand, suppleret i en vis udstrækning af subjektive beslutninger. Udnyttelse af...... reservoirer involverer en lang række interessenter med meget forskellige formål (f.eks. kunstig vanding, vandkraft, vandforsyning mv.), og optimeringsteknik kan langt bedre lede frem til afbalancerede løsninger af de ofte modstridende interesser. Afhandlingen foreslår en række tiltag, hvormed traditionelle...

  14. [Research progress on phosphorus budgets and regulations in reservoirs].

    Science.gov (United States)

    Shen, Xiao; Li, Xu; Zhang, Wang-shou

    2014-12-01

    Phosphorus is an important limiting factor of water eutrophication. A clear understanding of its budget and regulated method is fundamental for reservoir ecological health. In order to pro- mote systematic research further and improve phosphorus regulation system, the budget balance of reservoir phosphorus and its influencing factors were concluded, as well as conventional regulation and control measures. In general, the main phosphorus sources of reservoirs include upstream input, overland runoff, industrial and domestic wastewater, aquaculture, atmospheric deposition and sediment release. Upstream input is the largest phosphorus source among them. The principal output path of phosphorus is the flood discharge, the emission load of which is mainly influenced by drainage patterns. In addition, biological harvest also can export a fraction of phosphorus. There are some factors affecting the reservoir phosphorus balance, including reservoirs' function, hydrological conditions, physical and chemical properties of water, etc. Therefore, the phosphorus budgets of different reservoirs vary greatly, according to different seasons and regions. In order to reduce the phosphorus loading in reservoirs, some methods are carried out, including constructed wetlands, prefix reservoir, sediment dredging, biomanipulation, etc. Different methods need to be chosen and combined according to different reservoirs' characteristics and water quality management goals. Thus, in the future research, it is reasonable to highlight reservoir ecological characteristics and proceed to a complete and systematic analysis of the inherent complexity of phosphorus budget and its impact factors for the reservoirs' management. Besides, the interaction between phosphorus budget and other nutrients in reservoirs also needs to be conducted. It is fundamental to reduce the reservoirs' phosphorus loading to establish a scientific and improved management system based on those researches.

  15. Inaccuracy in traffic forecasts

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent; Holm, Mette K. Skamris; Buhl, Søren Ladegaard

    2006-01-01

    This paper presents results from the first statistically significant study of traffic forecasts in transportation infrastructure projects. The sample used is the largest of its kind, covering 210 projects in 14 nations worth US$58 billion. The study shows with very high statistical significance...... that forecasters generally do a poor job of estimating the demand for transportation infrastructure projects. The result is substantial downside financial and economic risk. Forecasts have not become more accurate over the 30-year period studied. If techniques and skills for arriving at accurate demand forecasts...... forecasting. Highly inaccurate traffic forecasts combined with large standard deviations translate into large financial and economic risks. But such risks are typically ignored or downplayed by planners and decision-makers, to the detriment of social and economic welfare. The paper presents the data...

  16. 2013 Gulf of Mexico Hypoxia Forecast

    Science.gov (United States)

    Scavia, Donald; Evans, Mary Anne; Obenour, Dan

    2013-01-01

    The Gulf of Mexico annual summer hypoxia forecasts are based on average May total nitrogen loads from the Mississippi River basin for that year. The load estimate, recently released by USGS, is 7,316 metric tons per day. Based on that estimate, we predict the area of this summer’s hypoxic zone to be 18,900 square kilometers (95% credible interval, 13,400 to 24,200), the 7th largest reported and about the size of New Jersey. Our forecast hypoxic volume is 74.5 km3 (95% credible interval, 51.5 to 97.0), also the 7th largest on record.

  17. 2014 Gulf of Mexico Hypoxia Forecast

    Science.gov (United States)

    Scavia, Donald; Evans, Mary Anne; Obenour, Dan

    2014-01-01

    The Gulf of Mexico annual summer hypoxia forecasts are based on average May total nitrogen loads from the Mississippi River basin for that year. The load estimate, recently released by USGS, is 4,761 metric tons per day. Based on that estimate, we predict the area of this summer’s hypoxic zone to be 14,000 square kilometers (95% credible interval, 8,000 to 20,000) – an “average year”. Our forecast hypoxic volume is 50 km3 (95% credible interval, 20 to 77).

  18. FORECASTING MODELS IN MANAGEMENT

    OpenAIRE

    Sindelar, Jiri

    2008-01-01

    This article deals with the problems of forecasting models. First part of the article is dedicated to definition of the relevant areas (vertical and horizontal pillar of definition) and then the forecasting model itself is defined; as article presents theoretical background for further primary research, this definition is crucial. Finally the position of forecasting models within the management system is identified. The paper is a part of the outputs of FEM CULS grant no. 1312/11/3121.

  19. Forecasting in Planning

    OpenAIRE

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively. Quantitative forecasting is illustrated with a brief overview of time series methods. Both qualitative and quantitative methods are illustrated by an example. The role and relative importance of forec...

  20. The strategy of professional forecasting

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    2006-01-01

    We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts...... and the realized state. If the market expects forecasters to report their posterior expectations honestly, then forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded. The second theory posits that forecasters compete in a forecasting...... contest with pre-specified rules. In a winner-take-all contest, equilibrium forecasts are excessively differentiated...

  1. Evaluation of statistical models for forecast errors from the HBV model

    Science.gov (United States)

    Engeland, Kolbjørn; Renard, Benjamin; Steinsland, Ingelin; Kolberg, Sjur

    2010-04-01

    SummaryThree statistical models for the forecast errors for inflow into the Langvatn reservoir in Northern Norway have been constructed and tested according to the agreement between (i) the forecast distribution and the observations and (ii) median values of the forecast distribution and the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order auto-regressive model was constructed for the forecast errors. The parameters were conditioned on weather classes. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order auto-regressive model was constructed for the forecast errors. For the third model positive and negative errors were modeled separately. The errors were first NQT-transformed before conditioning the mean error values on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: we wanted (a) the forecast distribution to be reliable; (b) the forecast intervals to be narrow; (c) the median values of the forecast distribution to be close to the observed values. Models 1 and 2 gave almost identical results. The median values improved the forecast with Nash-Sutcliffe R eff increasing from 0.77 for the original forecast to 0.87 for the corrected forecasts. Models 1 and 2 over-estimated the forecast intervals but gave the narrowest intervals. Their main drawback was that the distributions are less reliable than Model 3. For Model 3 the median values did not fit well since the auto-correlation was not accounted for. Since Model 3 did not benefit from the potential variance reduction that lies in bias estimation and removal it gave on average wider forecasts intervals than the two other models. At the same time Model 3 on average slightly under-estimated the forecast intervals, probably explained by the use of average measures to evaluate the fit.

  2. Hydrodynamics and Water Quality forecasting over a Cloud Computing environment: INDIGO-DataCloud

    Science.gov (United States)

    Aguilar Gómez, Fernando; de Lucas, Jesús Marco; García, Daniel; Monteoliva, Agustín

    2017-04-01

    Algae Bloom due to eutrophication is an extended problem for water reservoirs and lakes that impacts directly in water quality. It can create a dead zone that lacks enough oxygen to support life and it can also be human harmful, so it must be controlled in water masses for supplying, bathing or other uses. Hydrodynamic and Water Quality modelling can contribute to forecast the status of the water system in order to alert authorities before an algae bloom event occurs. It can be used to predict scenarios and find solutions to reduce the harmful impact of the blooms. High resolution models need to process a big amount of data using a robust enough computing infrastructure. INDIGO-DataCloud (https://www.indigo-datacloud.eu/) is an European Commission funded project that aims at developing a data and computing platform targeting scientific communities, deployable on multiple hardware and provisioned over hybrid (private or public) e-infrastructures. The project addresses the development of solutions for different Case Studies using different Cloud-based alternatives. In the first INDIGO software release, a set of components are ready to manage the deployment of services to perform N number of Delft3D simulations (for calibrating or scenario definition) over a Cloud Computing environment, using the Docker technology: TOSCA requirement description, Docker repository, Orchestrator, AAI (Authorization, Authentication) and OneData (Distributed Storage System). Moreover, the Future Gateway portal based on Liferay, provides an user-friendly interface where the user can configure the simulations. Due to the data approach of INDIGO, the developed solutions can contribute to manage the full data life cycle of a project, thanks to different tools to manage datasets or even metadata. Furthermore, the cloud environment contributes to provide a dynamic, scalable and easy-to-use framework for non-IT experts users. This framework is potentially capable to automatize the processing of

  3. Reservoir characterization of Pennsylvanian sandstone reservoirs. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Kelkar, M.

    1995-02-01

    This final report summarizes the progress during the three years of a project on Reservoir Characterization of Pennsylvanian Sandstone Reservoirs. The report is divided into three sections: (i) reservoir description; (ii) scale-up procedures; (iii) outcrop investigation. The first section describes the methods by which a reservoir can be described in three dimensions. The next step in reservoir description is to scale up reservoir properties for flow simulation. The second section addresses the issue of scale-up of reservoir properties once the spatial descriptions of properties are created. The last section describes the investigation of an outcrop.

  4. Mercury and methylmercury in reservoirs in Indiana

    Science.gov (United States)

    Risch, Martin R.; Fredericksen, Amanda L.

    2015-01-01

    Mercury (Hg) is an element that occurs naturally, but evidence suggests that human activities have resulted in increased amounts being released to the atmosphere and land surface. When Hg is converted to methylmercury (MeHg) in aquatic ecosystems, MeHg accumulates and increases in the food web so that some fish contain levels which pose a health risk to humans and wildlife that consume these fish. Reservoirs unlike natural lakes, are a part of river systems that are managed for flood control. Data compiled and interpreted for six flood-control reservoirs in Indiana showed a relation between Hg transport, MeHg formation in water, and MeHg in fish that was influenced by physical, chemical, and biological differences among the reservoirs. Existing information precludes a uniform comparison of Hg and MeHg in all reservoirs in the State, but factors and conditions were identified that can indicate where and when Hg and MeHg levels in reservoirs could be highest.

  5. Multiobjective Optimization Modeling Approach for Multipurpose Single Reservoir Operation

    Directory of Open Access Journals (Sweden)

    Iosvany Recio Villa

    2018-04-01

    Full Text Available The water resources planning and management discipline recognizes the importance of a reservoir’s carryover storage. However, mathematical models for reservoir operation that include carryover storage are scarce. This paper presents a novel multiobjective optimization modeling framework that uses the constraint-ε method and genetic algorithms as optimization techniques for the operation of multipurpose simple reservoirs, including carryover storage. The carryover storage was conceived by modifying Kritsky and Menkel’s method for reservoir design at the operational stage. The main objective function minimizes the cost of the total annual water shortage for irrigation areas connected to a reservoir, while the secondary one maximizes its energy production. The model includes operational constraints for the reservoir, Kritsky and Menkel’s method, irrigation areas, and the hydropower plant. The study is applied to Carlos Manuel de Céspedes reservoir, establishing a 12-month planning horizon and an annual reliability of 75%. The results highly demonstrate the applicability of the model, obtaining monthly releases from the reservoir that include the carryover storage, degree of reservoir inflow regulation, water shortages in irrigation areas, and the energy generated by the hydroelectric plant. The main product is an operational graph that includes zones as well as rule and guide curves, which are used as triggers for long-term reservoir operation.

  6. Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

    Energy Technology Data Exchange (ETDEWEB)

    Hitzman, D.O.; Stepp, A.K.; Dennis, D.M.; Graumann, L.R.

    2003-02-11

    This research program was directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal was to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with inorganic nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil-releasing agents.

  7. Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

    Energy Technology Data Exchange (ETDEWEB)

    Hitzman, D.O.; Bailey, S.A.; Stepp, A.K.

    2003-02-11

    This research program was directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal was to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with inorganic nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil releasing agents. The potential of the system will be illustrated and demonstrated by the example of biopolymer production on oil recovery.

  8. Diffuser Operations at Spring Hollow Reservoir

    OpenAIRE

    Gantzer, Paul Anthony

    2002-01-01

    Stratification is a natural occurrence in deep lakes and reservoirs. This phenomenon results in two distinct layers, the warmer, less dense epilimnion on top and the colder, denser, hypolimnion on the bottom. The epilimnion remains saturated with dissolved oxygen (DO) from mass transfer with the atmosphere, while the hypolimnion continues to undergo oxygen-depleting processes. During seasons of high oxygen demand the hypolimnion often becomes anoxic and results in the release of compounds,...

  9. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    Directory of Open Access Journals (Sweden)

    Christian Pierdzioch

    2012-11-01

    Full Text Available We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-herding of forecasters. Forecasts are consistent with herding (anti-herding of forecasters if forecasts are biased towards (away from the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time.

  10. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Ruelke

    2013-01-01

    We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) t......) the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time....

  11. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

    Directory of Open Access Journals (Sweden)

    Jun-He Yang

    2017-01-01

    Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  12. World Area Forecast System (WAFS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The World Area Forecast System (WAFS) is a worldwide system by which world area forecast centers provide aeronautical meteorological en-route forecasts in uniform...

  13. Fluid flow in gas condensate reservoirs. The interplay of forces and their relative strengths

    Energy Technology Data Exchange (ETDEWEB)

    Ursin, Jann-Rune [Stavanger University College, Department of Petroleum Engineering, PO Box 8002, Stavanger, 4068 (Norway)

    2004-02-01

    Natural production from gas condensate reservoirs is characterized by gas condensation and liquid dropout in the reservoir, first in the near wellbore volume, then as a cylindrical shaped region, dynamically developing into the reservoir volume. The effects of liquid condensation are reduced productivity and loss of production. Successful forecast of well productivity and reservoir production depends on detailed understanding of the effect of various forces acting on fluid flow in time and space. The production form gas condensate reservoirs is thus indirectly related to the interplay of fundamental forces, such as the viscosity, the capillary, the gravitational and the inertial force and their relative strengths, demonstrated by various dimensionless numbers. Dimensionless numbers are defined and calculated for all pressure and space coordinates in a test reservoir. Various regions are identified where certain forces are more important than others. Based on reservoir pressure development, liquid condensation and the numerical representation of dimensionless numbers, a conceptual understanding of a varying reservoir permeability has been reached.The material balance, the reservoir fluid flow and the wellbore flow calculations are performed on a cylindrical reservoir model. The ratios between fundamental forces are calculated and dimensionless numbers defined. The interplay of forces, demonstrated by these numbers, are calculated as function of radial dimension and reservoir pressure.

  14. Reservoirs on the mountain rivers and their safety

    Directory of Open Access Journals (Sweden)

    Ts.Z. Basilashvili

    2016-06-01

    Full Text Available Water resource issues and problems in the world's developing countries, present special challenges, as development of these countries significantly depends on the utilization of water resources. Georgia nestled between the Black Sea, Russia, and Turkey, and surrounded by the Caucasus Mountains, occupies a unique geographic space, which gives it strategic importance far beyond its size. Though blessed by its rich hydro resources, Georgia due to its uneven distribution, experiences some problems as the demand on water frequently doesn't coincide with water provision. As a result it causes acute deficit situation. Due to the global warming of the climate, it is expected that the fresh water amount will decrease in Georgia. This is why it is necessary to approach the use of water resources in a complex way by means of water reservoirs, which will enable attaining of a large economic effect. In the mountainous conditions filling of reservoirs take place in spring time, when snow and glaciers melt. In Georgia as in mountainous country, abundant rains take place, thus causing catastrophic flooding on rivers. In summer and winter water amount decreases 10 times and irrigation, water provision and energy production is impeded. Thus, the lack of water just like the excess amount of water causes damage. This is why it is needed to forecast water amount in water reservoirs for different periods of the year. But in a complex, mountainous terrain operative data of hydrometeorology is not sufficient for application of modern mathematical methods. We have elaborated multiple-factor statistical model for a forecast, which by means of different mathematical criteria and methods can simultaneously research the increase of the timeliness of forecasts and the level of their precision. We have obtained methodologies for short and long term forecasts of inflowing water properties in Georgia's main water reservoirs to further plan optimally and regulate water resources

  15. Forecasting in Planning

    NARCIS (Netherlands)

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively.

  16. Improving Garch Volatility Forecasts

    NARCIS (Netherlands)

    Klaassen, F.J.G.M.

    1998-01-01

    Many researchers use GARCH models to generate volatility forecasts. We show, however, that such forecasts are too variable. To correct for this, we extend the GARCH model by distinguishing two regimes with different volatility levels. GARCH effects are allowed within each regime, so that our model

  17. On density forecast evaluation

    NARCIS (Netherlands)

    Diks, C.

    2008-01-01

    Traditionally, probability integral transforms (PITs) have been popular means for evaluating density forecasts. For an ideal density forecast, the PITs should be uniformly distributed on the unit interval and independent. However, this is only a necessary condition, and not a sufficient one, as

  18. Forecast Accuracy Uncertainty and Momentum

    OpenAIRE

    Bing Han; Dong Hong; Mitch Warachka

    2009-01-01

    We demonstrate that stock price momentum and earnings momentum can result from uncertainty surrounding the accuracy of cash flow forecasts. Our model has multiple information sources issuing cash flow forecasts for a stock. The investor combines these forecasts into an aggregate cash flow estimate that has minimal mean-squared forecast error. This aggregate estimate weights each cash flow forecast by the estimated accuracy of its issuer, which is obtained from their past forecast errors. Mome...

  19. Appraisal of transport and deformation in shale reservoirs using natural noble gas tracers

    Energy Technology Data Exchange (ETDEWEB)

    Heath, Jason E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kuhlman, Kristopher L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Robinson, David G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bauer, Stephen J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gardner, William Payton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of Montana, Missoula, MT (United States)

    2015-09-01

    This report presents efforts to develop the use of in situ naturally-occurring noble gas tracers to evaluate transport mechanisms and deformation in shale hydrocarbon reservoirs. Noble gases are promising as shale reservoir diagnostic tools due to their sensitivity of transport to: shale pore structure; phase partitioning between groundwater, liquid, and gaseous hydrocarbons; and deformation from hydraulic fracturing. Approximately 1.5-year time-series of wellhead fluid samples were collected from two hydraulically-fractured wells. The noble gas compositions and isotopes suggest a strong signature of atmospheric contribution to the noble gases that mix with deep, old reservoir fluids. Complex mixing and transport of fracturing fluid and reservoir fluids occurs during production. Real-time laboratory measurements were performed on triaxially-deforming shale samples to link deformation behavior, transport, and gas tracer signatures. Finally, we present improved methods for production forecasts that borrow statistical strength from production data of nearby wells to reduce uncertainty in the forecasts.

  20. Evaluation of Maximum a Posteriori Estimation as Data Assimilation Method for Forecasting Infiltration-Inflow Affected Urban Runoff with Radar Rainfall Input

    DEFF Research Database (Denmark)

    Wied Pedersen, Jonas; Lund, Nadia Schou Vorndran; Borup, Morten

    2016-01-01

    High quality on-line flow forecasts are useful for real-time operation of urban drainage systems and wastewater treatment plants. This requires computationally efficient models, which are continuously updated with observed data to provide good initial conditions for the forecasts. This paper...... period of time that precedes the forecast. The method is illustrated for an urban catchment, where flow forecasts of 0–4 h are generated by applying a lumped linear reservoir model with three cascading reservoirs. Radar rainfall observations are used as input to the model. The effects of different prior...

  1. Real-time optimisation of the Hoa Binh reservoir, Vietnam

    DEFF Research Database (Denmark)

    Richaud, Bertrand; Madsen, Henrik; Rosbjerg, Dan

    2011-01-01

    -time optimisation. First, the simulation-optimisation framework is applied for optimising reservoir operating rules. Secondly, real-time and forecast information is used for on-line optimisation that focuses on short-term goals, such as flood control or hydropower generation, without compromising the deviation...... in the downstream part of the Red River, and at the same time to increase hydropower generation and to save water for the dry season. The real-time optimisation procedure further improves the efficiency of the reservoir operation and enhances the flexibility for the decision-making. Finally, the quality......Multi-purpose reservoirs often have to be managed according to conflicting objectives, which requires efficient tools for trading-off the objectives. This paper proposes a multi-objective simulation-optimisation approach that couples off-line rule curve optimisation with on-line real...

  2. Geothermal reservoir engineering

    CERN Document Server

    Grant, Malcolm Alister

    2011-01-01

    As nations alike struggle to diversify and secure their power portfolios, geothermal energy, the essentially limitless heat emanating from the earth itself, is being harnessed at an unprecedented rate.  For the last 25 years, engineers around the world tasked with taming this raw power have used Geothermal Reservoir Engineering as both a training manual and a professional reference.  This long-awaited second edition of Geothermal Reservoir Engineering is a practical guide to the issues and tasks geothermal engineers encounter in the course of their daily jobs. The bo

  3. Study of the impact of the uncertainties in petroleum reservoir behavior; Estudo do impacto de incertezas no desempenho de reservatorios de petroleo

    Energy Technology Data Exchange (ETDEWEB)

    Loschiavo, Roberto [PETROBRAS S.A., SE/AL (Brazil). Exploracao e Producao]. E-mail: rloschiavo@ep-seal.petrobras.com.br; Schiozer, Denis J. [Universidade Estadual de Campinas, SP (Brazil). Centro de Estudo do Petroleo (CEPETRO)]. E-mail: denis@cepetro.unicamp.br; Steagall, Daniel Escobar [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Engenharia Mecanica]. E-mail: steagall@dep.fem.unicamp.br

    2000-07-01

    Economic evaluation of a project as well as facilities design for oil exploitation is, in general, based on production forecasts. Since production forecast depends on several parameters that are not completely known, one should take a probabilistic approach for reservoir modeling and numerical flow simulation. With this research we propose a procedure to estimate probabilistic production forecasts profiles based on the decision tree technique. The most influencing parameters of a reservoir model are identified and combined to generate a number of realizations of the reservoirs. The combination of each branch of the decision tree defines the probability associated to each reservoir model. A computer program was developed to automatically generate the reservoir models, submit them to the numerical simulator, and process the results. Parallel computing was used to improve the performance of the procedure. (author)

  4. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Spatial Electric Load Forecasting Consumer Demand for Power and ReliabilityCoincidence and Load BehaviorLoad Curve and End-Use ModelingWeather and Electric LoadWeather Design Criteria and Forecast NormalizationSpatial Load Growth BehaviorSpatial Forecast Accuracy and Error MeasuresTrending MethodsSimulation Method: Basic ConceptsA Detailed Look at the Simulation MethodBasics of Computerized SimulationAnalytical Building Blocks for Spatial SimulationAdvanced Elements of Computerized SimulationHybrid Trending-Simulation MethodsAdvanced

  5. Mesoscale Modeling, Forecasting and Remote Sensing Research.

    Science.gov (United States)

    remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed

  6. Nagylengyel: an interesting reservoir. [Yugoslovia

    Energy Technology Data Exchange (ETDEWEB)

    Dedinszky, J

    1971-04-01

    The Nagylengyel oil field, discovered in 1951, has oil-producing formations mostly in the Upper-Triassic dolomites, in the Norian-Ractian transition formations, in the Upper-Cretaceous limestones and shales, and in the Miocene. The formation of the reservoir space occurred in many stages. A porous, cavernous fractured reservoir is developed in the Norian principal dolomite. A cavernous fractured reservoir exists in the Cretaceous limestone and in the Cretaceous shale and porous fractured reservoir is developed in the Miocene. The derivation of the model of the reservoir, and the conservative evaluation of the volume of the reservoir made it possible to use secondary recovery.

  7. Effects of water-supply reservoirs on streamflow in Massachusetts

    Science.gov (United States)

    Levin, Sara B.

    2016-10-06

    State and local water-resource managers need modeling tools to help them manage and protect water-supply resources for both human consumption and ecological needs. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a decision-support tool to estimate the effects of reservoirs on natural streamflow. The Massachusetts Reservoir Simulation Tool is a model that simulates the daily water balance of a reservoir. The reservoir simulation tool provides estimates of daily outflows from reservoirs and compares the frequency, duration, and magnitude of the volume of outflows from reservoirs with estimates of the unaltered streamflow that would occur if no dam were present. This tool will help environmental managers understand the complex interactions and tradeoffs between water withdrawals, reservoir operational practices, and reservoir outflows needed for aquatic habitats.A sensitivity analysis of the daily water balance equation was performed to identify physical and operational features of reservoirs that could have the greatest effect on reservoir outflows. For the purpose of this report, uncontrolled releases of water (spills or spillage) over the reservoir spillway were considered to be a proxy for reservoir outflows directly below the dam. The ratio of average withdrawals to the average inflows had the largest effect on spillage patterns, with the highest withdrawals leading to the lowest spillage. The size of the surface area relative to the drainage area of the reservoir also had an effect on spillage; reservoirs with large surface areas have high evaporation rates during the summer, which can contribute to frequent and long periods without spillage, even in the absence of water withdrawals. Other reservoir characteristics, such as variability of inflows, groundwater interactions, and seasonal demand patterns, had low to moderate effects on the frequency, duration, and magnitude of spillage. The

  8. Deterministic Echo State Networks Based Stock Price Forecasting

    Directory of Open Access Journals (Sweden)

    Jingpei Dan

    2014-01-01

    Full Text Available Echo state networks (ESNs, as efficient and powerful computational models for approximating nonlinear dynamical systems, have been successfully applied in financial time series forecasting. Reservoir constructions in standard ESNs rely on trials and errors in real applications due to a series of randomized model building stages. A novel form of ESN with deterministically constructed reservoir is competitive with standard ESN by minimal complexity and possibility of optimizations for ESN specifications. In this paper, forecasting performances of deterministic ESNs are investigated in stock price prediction applications. The experiment results on two benchmark datasets (Shanghai Composite Index and S&P500 demonstrate that deterministic ESNs outperform standard ESN in both accuracy and efficiency, which indicate the prospect of deterministic ESNs for financial prediction.

  9. About the National Forecast Chart

    Science.gov (United States)

    code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. The National Forecast Charts

  10. Dispersion Modeling Using Ensemble Forecasts Compared to ETEX Measurements.

    Science.gov (United States)

    Straume, Anne Grete; N'dri Koffi, Ernest; Nodop, Katrin

    1998-11-01

    Numerous numerical models are developed to predict long-range transport of hazardous air pollution in connection with accidental releases. When evaluating and improving such a model, it is important to detect uncertainties connected to the meteorological input data. A Lagrangian dispersion model, the Severe Nuclear Accident Program, is used here to investigate the effect of errors in the meteorological input data due to analysis error. An ensemble forecast, produced at the European Centre for Medium-Range Weather Forecasts, is then used as model input. The ensemble forecast members are generated by perturbing the initial meteorological fields of the weather forecast. The perturbations are calculated from singular vectors meant to represent possible forecast developments generated by instabilities in the atmospheric flow during the early part of the forecast. The instabilities are generated by errors in the analyzed fields. Puff predictions from the dispersion model, using ensemble forecast input, are compared, and a large spread in the predicted puff evolutions is found. This shows that the quality of the meteorological input data is important for the success of the dispersion model. In order to evaluate the dispersion model, the calculations are compared with measurements from the European Tracer Experiment. The model manages to predict the measured puff evolution concerning shape and time of arrival to a fairly high extent, up to 60 h after the start of the release. The modeled puff is still too narrow in the advection direction.

  11. Marine Point Forecasts

    Science.gov (United States)

    will link to the zone forecast and then allow further zooming to the point of interest whereas on the Honolulu, HI Chicago, IL Northern Indiana, IN Lake Charles, LA New Orleans, LA Boston, MA Caribou, ME

  12. Socioeconomic Forecasting : [Technical Summary

    Science.gov (United States)

    2012-01-01

    Because the traffic forecasts produced by the Indiana : Statewide Travel Demand Model (ISTDM) are driven by : the demographic and socioeconomic inputs to the model, : particular attention must be given to obtaining the most : accurate demographic and...

  13. NYHOPS Forecast Model Results

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — 3D Marine Nowcast/Forecast System for the New York Bight NYHOPS subdomain. Currents, waves, surface meteorology, and water conditions.

  14. Inflow forecasting at BPA

    Energy Technology Data Exchange (ETDEWEB)

    McManamon, A. [Bonneville Power Administration, Portland, OR (United States)

    2007-07-01

    The Columbia River Power System operates with consideration for flood control, endangered species, navigation, irrigation, water supply, recreation, other fish and wildlife concerns and power production. The Bonneville Power Association (BPA) located in Portland, Oregon is responsible for 35-40 per cent of the power consumed within the region. This presentation discussed inflow power concerns at BPA. The presentation illustrated elevational relief of projects; annual and daily variability; the hydrologic cycle; national river service weather forecasting service (NRSWFS); components of NRSWFS; and hydrologic forecast locations. Project operations and inventory were included along with a comparison of the 71-year average unregulated flow with regulated flow at the Dalles. Consistency between short-term and long-term forecasts and long-term streamflow forecasts were also illustrated in graphical format. The presentation also discussed the issue of reducing model and parameter uncertainty; reducing initial conditions uncertainty; snow updating; and reducing meteorological uncertainty. tabs., figs.

  15. CCAA seasonal forecasting

    International Development Research Centre (IDRC) Digital Library (Canada)

    Integrating meteorological and indigenous knowledge-based seasonal climate forecasts in ..... Explanation is based on spiritual and social values. Taught by .... that provided medicine and food became the subject of strict rules and practices ...

  16. Forecast Icing Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Forecast Icing Product (FIP) is an automatically-generated index suitable for depicting areas of potentially hazardous airframe icing. The FIP algorithm uses...

  17. Parallel reservoir simulator computations

    International Nuclear Information System (INIS)

    Hemanth-Kumar, K.; Young, L.C.

    1995-01-01

    The adaptation of a reservoir simulator for parallel computations is described. The simulator was originally designed for vector processors. It performs approximately 99% of its calculations in vector/parallel mode and relative to scalar calculations it achieves speedups of 65 and 81 for black oil and EOS simulations, respectively on the CRAY C-90

  18. unconventional natural gas reservoirs

    International Nuclear Information System (INIS)

    Correa G, Tomas F; Osorio, Nelson; Restrepo R, Dora P

    2009-01-01

    This work is an exploration about different unconventional gas reservoirs worldwide: coal bed methane, tight gas, shale gas and gas hydrate? describing aspects such as definition, reserves, production methods, environmental issues and economics. The overview also mentioned preliminary studies about these sources in Colombia.

  19. ENSEMBLE methods to reconcile disparate national long range dispersion forecasts

    DEFF Research Database (Denmark)

    Mikkelsen, Torben; Galmarini, S.; Bianconi, R.

    2003-01-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparatenational forecasts for long-range dispersion...... emergency and meteorological forecasting centres, which may choose to integrate them directly intooperational emergency information systems, or possibly use them as a basis for future system development.......ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparatenational forecasts for long-range dispersion....... ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidentalatmospheric release of radioactive material. A series of new decision-making “ENSEMBLE” procedures...

  20. Conditional Probabilistic Population Forecasting

    OpenAIRE

    Sanderson, W.C.; Scherbov, S.; O'Neill, B.C.; Lutz, W.

    2003-01-01

    Since policy makers often prefer to think in terms of scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy makers it allows them to answer "what if"...

  1. Conditional probabilistic population forecasting

    OpenAIRE

    Sanderson, Warren; Scherbov, Sergei; O'Neill, Brian; Lutz, Wolfgang

    2003-01-01

    Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because it allows them...

  2. Conditional Probabilistic Population Forecasting

    OpenAIRE

    Sanderson, Warren C.; Scherbov, Sergei; O'Neill, Brian C.; Lutz, Wolfgang

    2004-01-01

    Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because...

  3. EU pharmaceutical expenditure forecast

    OpenAIRE

    Urbinati, Duccio; Rémuzat, Cécile; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    Background and Objectives: With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States’ ph...

  4. Problems of Forecast

    OpenAIRE

    Kucharavy , Dmitry; De Guio , Roland

    2005-01-01

    International audience; The ability to foresee future technology is a key task of Innovative Design. The paper focuses on the obstacles to reliable prediction of technological evolution for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods is presented. The causes for the complexity of technology prediction are discussed in the context of reduction of the forecast errors. Second, using a contradiction analysis, a set of problems related to ...

  5. Application of seasonal forecasting for the drought forecasting in Catalonia (Spain)

    Science.gov (United States)

    Llasat, Maria-Carmen; Zaragoza, Albert; Aznar, Blanca; Cabot, Jordi

    2010-05-01

    Low flows and droughts are a hydro-climatic feature in Spain (Alvarez et al, 2008). The construction of dams as water reservoirs has been a usual tool to manage the water resources for agriculture and livestock, industries and human needs (MIMAM, 2000, 2007). The last drought that has affected Spain has last four years in Catalonia, from 2004 to the spring of 2008, and it has been particularly hard as a consequence of the precipitation deficit in the upper part of the rivers that nourish the main dams. This problem increases when the water scarcity affects very populated areas, like big cities. The Barcelona city, with more than 3.000.000 people concentrated in the downtown and surrounding areas is a clear example. One of the objectives of the SOSTAQUA project is to improve the water resources management in real time, in order to improve the water supply in the cities in the framework of sustainable development. The work presented here deals with the application of seasonal forecasting to improve the water management in Catalonia, particularly in drought conditions. A seasonal prediction index has been created as a linear combination of climatic data and the ECM4 prediction that has been validated too. This information has implemented into a hydrological model and it has been applied to the last drought considering the real water demands of population, as well as to the water storage evolution in the last months. It has been found a considerable advance in the forecasting of water volume into reservoirs. The advantage of this methodology is that it only requires seasonal forecasting free through internet. Due to the fact that the principal rivers that supply water to Barcelona, birth on the Pyrenees and Pre-Pyrenees region, the analysis and precipitation forecasting is focused on this region (Zaragoza, 2008).

  6. Forecast communication through the newspaper Part 2: perceptions of uncertainty

    Science.gov (United States)

    Harris, Andrew J. L.

    2015-04-01

    In the first part of this review, I defined the media filter and how it can operate to frame and blame the forecaster for losses incurred during an environmental disaster. In this second part, I explore the meaning and role of uncertainty when a forecast, and its basis, is communicated through the response and decision-making chain to the newspaper, especially during a rapidly evolving natural disaster which has far-reaching business, political, and societal impacts. Within the media-based communication system, there remains a fundamental disconnect of the definition of uncertainty and the interpretation of the delivered forecast between various stakeholders. The definition and use of uncertainty differs especially between scientific, media, business, and political stakeholders. This is a serious problem for the scientific community when delivering forecasts to the public though the press. As reviewed in Part 1, the media filter can result in a negative frame, which itself is a result of bias, slant, spin, and agenda setting introduced during passage of the forecast and its uncertainty through the media filter. The result is invariably one of anger and fury, which causes loss of credibility and blaming of the forecaster. Generation of a negative frame can be aided by opacity of the decision-making process that the forecast is used to support. The impact of the forecast will be determined during passage through the decision-making chain where the precautionary principle and cost-benefit analysis, for example, will likely be applied. Choice of forecast delivery format, vehicle of communication, syntax of delivery, and lack of follow-up measures can further contribute to causing the forecast and its role to be misrepresented. Follow-up measures to negative frames may include appropriately worded press releases and conferences that target forecast misrepresentation or misinterpretation in an attempt to swing the slant back in favor of the forecaster. Review of

  7. Hydro-economic assessment of hydrological forecasting systems

    Science.gov (United States)

    Boucher, M.-A.; Tremblay, D.; Delorme, L.; Perreault, L.; Anctil, F.

    2012-01-01

    SummaryAn increasing number of publications show that ensemble hydrological forecasts exhibit good performance when compared to observed streamflow. Many studies also conclude that ensemble forecasts lead to a better performance than deterministic ones. This investigation takes one step further by not only comparing ensemble and deterministic forecasts to observed values, but by employing the forecasts in a stochastic decision-making assistance tool for hydroelectricity production, during a flood event on the Gatineau River in Canada. This allows the comparison between different types of forecasts according to their value in terms of energy, spillage and storage in a reservoir. The motivation for this is to adopt the point of view of an end-user, here a hydroelectricity production society. We show that ensemble forecasts exhibit excellent performances when compared to observations and are also satisfying when involved in operation management for electricity production. Further improvement in terms of productivity can be reached through the use of a simple post-processing method.

  8. Web3DGIS-Based System for Reservoir Landslide Monitoring and Early Warning

    Directory of Open Access Journals (Sweden)

    Huang Huang

    2016-02-01

    Full Text Available Landslides are the most frequent type of natural disaster, and they bring about large-scale damage and are a threat to human lives and infrastructure; therefore, the ability to conduct real-time monitoring and early warning is important. In this study, a Web3DGIS (Web3D geographic information systems system for monitoring and forecasting landslides was developed using the Danjiangkou Reservoir area as a case study. The development of this technique involved system construction, functional design, organizing and managing multi-source spatial data, and implementing a forecasting plan and landslide-forecasting model. By integrating sensor technologies, spatial information technologies, 3D visualization technologies, and a landslide-forecasting model, the results of this study provide a tool for real-time monitoring at potential landslide sites. When relevant data from these sites reach threshold values, the model automatically initiates forecasting procedures, and sends information to disaster prevention sectors for emergency management.

  9. Comparison of static and dynamic resilience for a multipurpose reservoir operation

    Science.gov (United States)

    Simonovic, Slobodan P.; Arunkumar, R.

    2016-11-01

    Reliability, resilience, and vulnerability are the traditional risk measures used to assess the performance of a reservoir system. Among these measures, resilience is used to assess the ability of a reservoir system to recover from a failure event. However, the time-independent static resilience does not consider the system characteristics, interaction of various individual components and does not provide much insight into reservoir performance from the beginning of the failure event until the full performance recovery. Knowledge of dynamic reservoir behavior under the disturbance offers opportunities for proactive and/or reactive adaptive response that can be selected to maximize reservoir resilience. A novel measure is required to provide insight into the dynamics of reservoir performance based on the reservoir system characteristics and its adaptive capacity. The reservoir system characteristics include, among others, reservoir storage curve, reservoir inflow, reservoir outflow capacity, and reservoir operating rules. The reservoir adaptive capacity can be expressed using various impacts of reservoir performance under the disturbance (like reservoir release for meeting a particular demand, socioeconomic consequences of reservoir performance, or resulting environmental state of the river upstream and downstream from the reservoir). Another way of expressing reservoir adaptive capacity to a disturbing event may include aggregated measures like reservoir robustness, redundancy, resourcefulness, and rapidity. A novel measure that combines reservoir performance and its adaptive capacity is proposed in this paper and named "dynamic resilience." The paper also proposes a generic simulation methodology for quantifying reservoir resilience as a function of time. The proposed resilience measure is applied to a single multipurpose reservoir operation and tested for a set of failure scenarios. The dynamic behavior of reservoir resilience is captured using the system

  10. Real-time reservoir operation considering non-stationary inflow prediction

    Science.gov (United States)

    Zhao, J.; Xu, W.; Cai, X.; Wang, Z.

    2011-12-01

    Stationarity of inflow has been a basic assumption for reservoir operation rule design, which is now facing challenges due to climate change and human interferences. This paper proposes a modeling framework to incorporate non-stationary inflow prediction for optimizing the hedging operation rule of large reservoirs with multiple-year flow regulation capacity. A multi-stage optimization model is formulated and a solution algorithm based on the optimality conditions is developed to incorporate non-stationary annual inflow prediction through a rolling, dynamic framework that updates the prediction from period to period and adopt the updated prediction in reservoir operation decision. The prediction model is ARIMA(4,1,0), in which parameter 4 stands for the order of autoregressive, 1 represents a linear trend, and 0 is the order of moving average. The modeling framework and solution algorithm is applied to the Miyun reservoir in China, determining a yearly operating schedule during the period from 1996 to 2009, during which there was a significant declining trend of reservoir inflow. Different operation policy scenarios are modeled, including standard operation policy (SOP, matching the current demand as much as possible), hedging rule (i.e., leaving a certain amount of water for future to avoid large risk of water deficit) with forecast from ARIMA (HR-1), hedging (HR) with perfect forecast (HR-2 ). Compared to the results of these scenarios to that of the actual reservoir operation (AO), the utility of the reservoir operation under HR-1 is 3.0% lower than HR-2, but 3.7% higher than the AO and 14.4% higher than SOP. Note that the utility under AO is 10.3% higher than that under SOP, which shows that a certain level of hedging under some inflow prediction or forecast was used in the real-world operation. Moreover, the impacts of discount rate and forecast uncertainty level on the operation will be discussed.

  11. APPLICATION OF INTEGRATED RESERVOIR MANAGEMENT AND RESERVOIR CHARACTERIZATION

    Energy Technology Data Exchange (ETDEWEB)

    Jack Bergeron; Tom Blasingame; Louis Doublet; Mohan Kelkar; George Freeman; Jeff Callard; David Moore; David Davies; Richard Vessell; Brian Pregger; Bill Dixon; Bryce Bezant

    2000-03-01

    Reservoir performance and characterization are vital parameters during the development phase of a project. Infill drilling of wells on a uniform spacing, without regard to characterization does not optimize development because it fails to account for the complex nature of reservoir heterogeneities present in many low permeability reservoirs, especially carbonate reservoirs. These reservoirs are typically characterized by: (1) large, discontinuous pay intervals; (2) vertical and lateral changes in reservoir properties; (3) low reservoir energy; (4) high residual oil saturation; and (5) low recovery efficiency. The operational problems they encounter in these types of reservoirs include: (1) poor or inadequate completions and stimulations; (2) early water breakthrough; (3) poor reservoir sweep efficiency in contacting oil throughout the reservoir as well as in the nearby well regions; (4) channeling of injected fluids due to preferential fracturing caused by excessive injection rates; and (5) limited data availability and poor data quality. Infill drilling operations only need target areas of the reservoir which will be economically successful. If the most productive areas of a reservoir can be accurately identified by combining the results of geological, petrophysical, reservoir performance, and pressure transient analyses, then this ''integrated'' approach can be used to optimize reservoir performance during secondary and tertiary recovery operations without resorting to ''blanket'' infill drilling methods. New and emerging technologies such as geostatistical modeling, rock typing, and rigorous decline type curve analysis can be used to quantify reservoir quality and the degree of interwell communication. These results can then be used to develop a 3-D simulation model for prediction of infill locations. The application of reservoir surveillance techniques to identify additional reservoir ''pay'' zones

  12. Developing Novel Reservoir Rule Curves Using Seasonal Inflow Projections

    Science.gov (United States)

    Tseng, Hsin-yi; Tung, Ching-pin

    2015-04-01

    Due to significant seasonal rainfall variations, reservoirs and their flexible operational rules are indispensable to Taiwan. Furthermore, with the intensifying impacts of climate change on extreme climate, the frequency of droughts in Taiwan has been increasing in recent years. Drought is a creeping phenomenon, the slow onset character of drought makes it difficult to detect at an early stage, and causes delays on making the best decision of allocating water. For these reasons, novel reservoir rule curves using projected seasonal streamflow are proposed in this study, which can potentially reduce the adverse effects of drought. This study dedicated establishing new rule curves which consider both current available storage and anticipated monthly inflows with leading time of two months to reduce the risk of water shortage. The monthly inflows are projected based on the seasonal climate forecasts from Central Weather Bureau (CWB), which a weather generation model is used to produce daily weather data for the hydrological component of the GWLF. To incorporate future monthly inflow projections into rule curves, this study designs a decision flow index which is a linear combination of current available storage and inflow projections with leading time of 2 months. By optimizing linear relationship coefficients of decision flow index, the shape of rule curves and the percent of water supply in each zone, the best rule curves to decrease water shortage risk and impacts can be developed. The Shimen Reservoir in the northern Taiwan is used as a case study to demonstrate the proposed method. Existing rule curves (M5 curves) of Shimen Reservoir are compared with two cases of new rule curves, including hindcast simulations and historic seasonal forecasts. The results show new rule curves can decrease the total water shortage ratio, and in addition, it can also allocate shortage amount to preceding months to avoid extreme shortage events. Even though some uncertainties in

  13. Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

    Energy Technology Data Exchange (ETDEWEB)

    D. O. Hitzman; A. K. Stepp; D. M. Dennis; L. R. Graumann

    2003-03-31

    This research program is directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal is to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil-releasing agents. Experimental laboratory work is underway. Microbial cultures have been isolated from produced water samples. Comparative laboratory studies demonstrating in situ production of microbial products as oil recovery agents were conducted in sand packs with natural field waters with cultures and conditions representative of oil reservoirs. Field pilot studies are underway.

  14. A Drought Early Warning System Using System Dynamics Model and Seasonal Climate Forecasts: a case study in Hsinchu, Taiwan.

    Science.gov (United States)

    Tien, Yu-Chuan; Tung, Ching-Ping; Liu, Tzu-Ming; Lin, Chia-Yu

    2016-04-01

    In the last twenty years, Hsinchu, a county of Taiwan, has experienced a tremendous growth in water demand due to the development of Hsinchu Science Park. In order to fulfill the water demand, the government has built the new reservoir, Baoshan second reservoir. However, short term droughts still happen. One of the reasons is that the water level of the reservoirs in Hsinchu cannot be reasonably forecasted, which sometimes even underestimates the severity of drought. The purpose of this study is to build a drought early warning system that projects the water levels of two important reservoirs, Baoshan and Baoshan second reservoir, and also the spatial distribution of water shortagewith the lead time of three months. Furthermore, this study also attempts to assist the government to improve water resources management. Hence, a system dynamics model of Touchien River, which is the most important river for public water supply in Hsinchu, is developed. The model consists of several important subsystems, including two reservoirs, water treatment plants and agricultural irrigation districts. Using the upstream flow generated by seasonal weather forecasting data, the model is able to simulate the storage of the two reservoirs and the distribution of water shortage. Moreover, the model can also provide the information under certain emergency scenarios, such as the accident or failure of a water treatment plant. At last, the performance of the proposed method and the original water resource management method that the government used were also compared. Keyword: Water Resource Management, Hydrology, Seasonal Climate Forecast, Reservoir, Early Warning, Drought

  15. Modeling of Turbidity Variation in Two Reservoirs Connected by a Water Transfer Tunnel in South Korea

    Directory of Open Access Journals (Sweden)

    Jae Chung Park

    2017-06-01

    Full Text Available The Andong and Imha reservoirs in South Korea are connected by a water transfer tunnel. The turbidity of the Imha reservoir is much higher than that of the Andong reservoir. Thus, it is necessary to examine the movement of turbidity between the two reservoirs via the water transfer tunnel. The aim of this study was to investigate the effect of the water transfer tunnel on the turbidity behavior of the two connecting reservoirs and to further understand the effect of reservoir turbidity distribution as a function of the selective withdrawal depth. This study applied the CE-QUAL-W2, a water quality and 2-dimensional hydrodynamic model, for simulating the hydrodynamic processes of the two reservoirs. Results indicate that, in the Andong reservoir, the turbidity of the released water with the water transfer tunnel was similar to that without the tunnel. However, in the Imha reservoir, the turbidity of the released water with the water transfer tunnel was lower than that without the tunnel. This can be attributed to the higher capacity of the Andong reservoir, which has double the storage of the Imha reservoir. Withdrawal turbidity in the Imha reservoir was investigated using the water transfer tunnel. This study applied three withdrawal selections as elevation (EL. 141.0 m, 146.5 m, and 152.0 m. The highest withdrawal turbidity resulted in EL. 141.0 m, which indicates that the high turbidity current is located at a vertical depth of about 20–30 m because of the density difference. These results will be helpful for understanding the release and selective withdrawal turbidity behaviors for a water transfer tunnel between two reservoirs.

  16. Decision Support System for Reservoir Management and Operation in Africa

    Science.gov (United States)

    Navar, D. A.

    2016-12-01

    Africa is currently experiencing a surge in dam construction for flood control, water supply and hydropower production, but ineffective reservoir management has caused problems in the region, such as water shortages, flooding and loss of potential hydropower generation. Our research aims to remedy ineffective reservoir management by developing a novel Decision Support System(DSS) to equip water managers with a technical planning tool based on the state of the art in hydrological sciences. The DSS incorporates a climate forecast model, a hydraulic model of the watershed, and an optimization model to effectively plan for the operation of a system of cascade large-scale reservoirs for hydropower production, while treating water supply and flood control as constraints. Our team will use the newly constructed hydropower plants in the Omo Gibe basin of Ethiopia as the test case. Using the basic HIDROTERM software developed in Brazil, the General Algebraic Modeling System (GAMS) utilizes a combination of linear programing (LP) and non-linear programming (NLP) in conjunction with real time hydrologic and energy demand data to optimize the monthly and daily operations of the reservoir system. We compare the DSS model results with the current reservoir operating policy used by the water managers of that region. We also hope the DSS will eliminate the current dangers associated with the mismanagement of large scale water resources projects in Africa.

  17. Influence of break structures on the distribution of radionuclides in bottom sediments of the Kyiv reservoir

    International Nuclear Information System (INIS)

    Shestopalov, V.M.; Lyal'ko, V.I.; Fedorovskij, A.D.; Sirenko, L.A.; Khodorovskij, A.Ya.

    2000-01-01

    We study the distribution of radionuclides in bottom sediments of the Kyiv reservoir on the basis of research of adjacent territory break - block structures with deciphering space-born images and ground measurements and forecast the occurrence of extreme situations due to the redistribution of bottom water flows and sediments of radionuclides

  18. Chalk as a reservoir

    DEFF Research Database (Denmark)

    Fabricius, Ida Lykke

    , and the best reservoir properties are typically found in mudstone intervals. Chalk mudstones vary a lot though. The best mudstones are purely calcitic, well sorted and may have been redeposited by traction currents. Other mudstones are rich in very fine grained silica, which takes up pore space and thus...... basin, so stylolite formation in the chalk is controlled by effective burial stress. The stylolites are zones of calcite dissolution and probably are the source of calcite for porefilling cementation which is typical in water zone chalk and also affect the reservoirs to different extent. The relatively...... have hardly any stylolites and can have porosity above 40% or even 50% and thus also have relatively high permeability. Such intervals have the problem though, that increasing effective stress caused by hydrocarbon production results in mechanical compaction and overall subsidence. Most other chalk...

  19. Bathymetry and capacity of Shawnee Reservoir, Oklahoma, 2016

    Science.gov (United States)

    Ashworth, Chad E.; Smith, S. Jerrod; Smith, Kevin A.

    2017-02-13

    Shawnee Reservoir (locally known as Shawnee Twin Lakes) is a man-made reservoir on South Deer Creek with a drainage area of 32.7 square miles in Pottawatomie County, Oklahoma. The reservoir consists of two lakes connected by an equilibrium channel. The southern lake (Shawnee City Lake Number 1) was impounded in 1935, and the northern lake (Shawnee City Lake Number 2) was impounded in 1960. Shawnee Reservoir serves as a municipal water supply, and water is transferred about 9 miles by gravity to a water treatment plant in Shawnee, Oklahoma. Secondary uses of the reservoir are for recreation, fish and wildlife habitat, and flood control. Shawnee Reservoir has a normal-pool elevation of 1,069.0 feet (ft) above North American Vertical Datum of 1988 (NAVD 88). The auxiliary spillway, which defines the flood-pool elevation, is at an elevation of 1,075.0 ft.The U.S. Geological Survey (USGS), in cooperation with the City of Shawnee, has operated a real-time stage (water-surface elevation) gage (USGS station 07241600) at Shawnee Reservoir since 2006. For the period of record ending in 2016, this gage recorded a maximum stage of 1,078.1 ft on May 24, 2015, and a minimum stage of 1,059.1 ft on April 10–11, 2007. This gage did not report reservoir storage prior to this report (2016) because a sufficiently detailed and thoroughly documented bathymetric (reservoir-bottom elevation) survey and corresponding stage-storage relation had not been published. A 2011 bathymetric survey with contours delineated at 5-foot intervals was published in Oklahoma Water Resources Board (2016), but that publication did not include a stage-storage relation table. The USGS, in cooperation with the City of Shawnee, performed a bathymetric survey of Shawnee Reservoir in 2016 and released the bathymetric-survey data in 2017. The purposes of the bathymetric survey were to (1) develop a detailed bathymetric map of the reservoir and (2) determine the relations between stage and reservoir storage

  20. Streamflow Forecasting Using Nuero-Fuzzy Inference System

    Science.gov (United States)

    Nanduri, U. V.; Swain, P. C.

    2005-12-01

    The prediction of flow into a reservoir is fundamental in water resources planning and management. The need for timely and accurate streamflow forecasting is widely recognized and emphasized by many in water resources fraternity. Real-time forecasts of natural inflows to reservoirs are of particular interest for operation and scheduling. The physical system of the river basin that takes the rainfall as an input and produces the runoff is highly nonlinear, complicated and very difficult to fully comprehend. The system is influenced by large number of factors and variables. The large spatial extent of the systems forces the uncertainty into the hydrologic information. A variety of methods have been proposed for forecasting reservoir inflows including conceptual (physical) and empirical (statistical) models (WMO 1994), but none of them can be considered as unique superior model (Shamseldin 1997). Owing to difficulties of formulating reasonable non-linear watershed models, recent attempts have resorted to Neural Network (NN) approach for complex hydrologic modeling. In recent years the use of soft computing in the field of hydrological forecasting is gaining ground. The relatively new soft computing technique of Adaptive Neuro-Fuzzy Inference System (ANFIS), developed by Jang (1993) is able to take care of the non-linearity, uncertainty, and vagueness embedded in the system. It is a judicious combination of the Neural Networks and fuzzy systems. It can learn and generalize highly nonlinear and uncertain phenomena due to the embedded neural network (NN). NN is efficient in learning and generalization, and the fuzzy system mimics the cognitive capability of human brain. Hence, ANFIS can learn the complicated processes involved in the basin and correlate the precipitation to the corresponding discharge. In the present study, one step ahead forecasts are made for ten-daily flows, which are mostly required for short term operational planning of multipurpose reservoirs. A

  1. Work reservoirs in thermodynamics

    International Nuclear Information System (INIS)

    Anacleto, Joaquim

    2010-01-01

    We stress the usefulness of the work reservoir in the formalism of thermodynamics, in particular in the context of the first law. To elucidate its usefulness, the formalism is then applied to the Joule expansion and other peculiar and instructive experimental situations, clarifying the concepts of configuration and dissipative work. The ideas and discussions presented in this study are primarily intended for undergraduate students, but they might also be useful to graduate students, researchers and teachers.

  2. Work reservoirs in thermodynamics

    Science.gov (United States)

    Anacleto, Joaquim

    2010-05-01

    We stress the usefulness of the work reservoir in the formalism of thermodynamics, in particular in the context of the first law. To elucidate its usefulness, the formalism is then applied to the Joule expansion and other peculiar and instructive experimental situations, clarifying the concepts of configuration and dissipative work. The ideas and discussions presented in this study are primarily intended for undergraduate students, but they might also be useful to graduate students, researchers and teachers.

  3. OPTIMIZATION OF INFILL DRILLING IN NATURALLY-FRACTURED TIGHT-GAS RESERVOIRS

    Energy Technology Data Exchange (ETDEWEB)

    Lawrence W. Teufel; Her-Yuan Chen; Thomas W. Engler; Bruce Hart

    2004-05-01

    A major goal of industry and the U.S. Department of Energy (DOE) fossil energy program is to increase gas reserves in tight-gas reservoirs. Infill drilling and hydraulic fracture stimulation in these reservoirs are important reservoir management strategies to increase production and reserves. Phase II of this DOE/cooperative industry project focused on optimization of infill drilling and evaluation of hydraulic fracturing in naturally-fractured tight-gas reservoirs. The cooperative project involved multidisciplinary reservoir characterization and simulation studies to determine infill well potential in the Mesaverde and Dakota sandstone formations at selected areas in the San Juan Basin of northwestern New Mexico. This work used the methodology and approach developed in Phase I. Integrated reservoir description and hydraulic fracture treatment analyses were also conducted in the Pecos Slope Abo tight-gas reservoir in southeastern New Mexico and the Lewis Shale in the San Juan Basin. This study has demonstrated a methodology to (1) describe reservoir heterogeneities and natural fracture systems, (2) determine reservoir permeability and permeability anisotropy, (3) define the elliptical drainage area and recoverable gas for existing wells, (4) determine the optimal location and number of new in-fill wells to maximize economic recovery, (5) forecast the increase in total cumulative gas production from infill drilling, and (6) evaluate hydraulic fracture simulation treatments and their impact on well drainage area and infill well potential. Industry partners during the course of this five-year project included BP, Burlington Resources, ConocoPhillips, and Williams.

  4. Space Weather Forecasting at IZMIRAN

    Science.gov (United States)

    Gaidash, S. P.; Belov, A. V.; Abunina, M. A.; Abunin, A. A.

    2017-12-01

    Since 1998, the Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation (IZMIRAN) has had an operating heliogeophysical service—the Center for Space Weather Forecasts. This center transfers the results of basic research in solar-terrestrial physics into daily forecasting of various space weather parameters for various lead times. The forecasts are promptly available to interested consumers. This article describes the center and the main types of forecasts it provides: solar and geomagnetic activity, magnetospheric electron fluxes, and probabilities of proton increases. The challenges associated with the forecasting of effects of coronal mass ejections and coronal holes are discussed. Verification data are provided for the center's forecasts.

  5. Advantageous Reservoir Characterization Technology in Extra Low Permeability Oil Reservoirs

    Directory of Open Access Journals (Sweden)

    Yutian Luo

    2017-01-01

    Full Text Available This paper took extra low permeability reservoirs in Dagang Liujianfang Oilfield as an example and analyzed different types of microscopic pore structures by SEM, casting thin sections fluorescence microscope, and so on. With adoption of rate-controlled mercury penetration, NMR, and some other advanced techniques, based on evaluation parameters, namely, throat radius, volume percentage of mobile fluid, start-up pressure gradient, and clay content, the classification and assessment method of extra low permeability reservoirs was improved and the parameter boundaries of the advantageous reservoirs were established. The physical properties of reservoirs with different depth are different. Clay mineral variation range is 7.0%, and throat radius variation range is 1.81 μm, and start pressure gradient range is 0.23 MPa/m, and movable fluid percentage change range is 17.4%. The class IV reservoirs account for 9.56%, class II reservoirs account for 12.16%, and class III reservoirs account for 78.29%. According to the comparison of different development methods, class II reservoir is most suitable for waterflooding development, and class IV reservoir is most suitable for gas injection development. Taking into account the gas injection in the upper section of the reservoir, the next section of water injection development will achieve the best results.

  6. Synergizing Crosswell Seismic and Electromagnetic Techniques for Enhancing Reservoir Characterization

    KAUST Repository

    Katterbauer, Klemens

    2015-11-18

    Increasing complexity of hydrocarbon projects and the request for higher recovery rates have driven the oil-and-gas industry to look for a more-detailed understanding of the subsurface formation to optimize recovery of oil and profitability. Despite the significant successes of geophysical techniques in determining changes within the reservoir, the benefits from individually mapping the information are limited. Although seismic techniques have been the main approach for imaging the subsurface, the weak density contrast between water and oil has made electromagnetic (EM) technology an attractive complement to improve fluid distinction, especially for high-saline water. This crosswell technology assumes greater importance for obtaining higher-resolution images of the interwell regions to more accurately characterize the reservoir and track fluid-front developments. In this study, an ensemble-Kalman-based history-matching framework is proposed for directly incorporating crosswell time-lapse seismic and EM data into the history-matching process. The direct incorporation of the time-lapse seismic and EM data into the history-matching process exploits the complementarity of these data to enhance subsurface characterization, to incorporate interwell information, and to avoid biases that may be incurred from separate inversions of the geophysical data for attributes. An extensive analysis with 2D and realistic 3D reservoirs illustrates the robustness and enhanced forecastability of critical reservoir variables. The 2D reservoir provides a better understanding of the connection between fluid discrimination and enhanced history matches, and the 3D reservoir demonstrates its applicability to a realistic reservoir. History-matching enhancements (in terms of reduction in the history-matching error) when incorporating both seismic and EM data averaged approximately 50% for the 2D case, and approximately 30% for the 3D case, and permeability estimates were approximately 25

  7. Climate Change Assessment of Precipitation in Tandula Reservoir System

    Science.gov (United States)

    Jaiswal, Rahul Kumar; Tiwari, H. L.; Lohani, A. K.

    2018-02-01

    The precipitation is the principle input of hydrological cycle affect availability of water in spatial and temporal scale of basin due to widely accepted climate change. The present study deals with the statistical downscaling using Statistical Down Scaling Model for rainfall of five rain gauge stations (Ambagarh, Bhanpura, Balod, Chamra and Gondli) in Tandula, Kharkhara and Gondli reservoirs of Chhattisgarh state of India to forecast future rainfall in three different periods under SRES A1B and A2 climatic forcing conditions. In the analysis, twenty-six climatic variables obtained from National Centers for Environmental Prediction were used and statistically tested for selection of best-fit predictors. The conditional process based statistical correlation was used to evolve multiple linear relations in calibration for period of 1981-1995 was tested with independent data of 1996-2003 for validation. The developed relations were further used to predict future rainfall scenarios for three different periods 2020-2035 (FP-1), 2046-2064 (FP-2) and 2081-2100 (FP-3) and compared with monthly rainfalls during base period (1981-2003) for individual station and all three reservoir catchments. From the analysis, it has been found that most of the rain gauge stations and all three reservoir catchments may receive significant less rainfall in future. The Thiessen polygon based annual and seasonal rainfall for different catchments confirmed a reduction of seasonal rainfall from 5.1 to 14.1% in Tandula reservoir, 11-19.2% in Kharkhara reservoir and 15.1-23.8% in Gondli reservoir. The Gondli reservoir may be affected the most in term of water availability in future prediction periods.

  8. Oral fluoride reservoirs and the prevention of dental caries.

    Science.gov (United States)

    Vogel, Gerald Lee

    2011-01-01

    Current models for increasing the anti-caries effects of fluoride (F) agents emphasize the importance of maintaining a cariostatic concentration of F in oral fluids. The concentration of F in oral fluids is maintained by the release of this ion from bioavailable reservoirs on the teeth, oral mucosa and - most importantly, because of its association with the caries process - dental plaque. Oral F reservoirs appear to be of two types: (1) mineral reservoirs, in particular calcium fluoride or phosphate-contaminated 'calcium-fluoride-like' deposits; (2) biological reservoirs, in particular (with regard to dental plaque) F held to bacteria or bacterial fragments via calcium-fluoride bonds. The fact that all these reservoirs are mediated by calcium implies that their formation is limited by the low concentration of calcium in oral fluids. By using novel procedures which overcome this limitation, the formation of these F reservoirs after topical F application can be greatly increased. Although these increases are associated with substantive increases in salivary and plaque fluid F, and hence a potential increase in cariostatic effect, it is unclear if such changes are related to the increases in the amount of these reservoirs, or changes in the types of F deposits formed. New techniques have been developed for identifying and quantifying these deposits which should prove useful in developing agents that enhance formation of oral F reservoirs with optimum F release characteristics. Such research offers the prospect of decreasing the F content of topical agents while simultaneously increasing their cariostatic effect. Copyright © 2011 S. Karger AG, Basel.

  9. Optimization In Searching Daily Rule Curve At Mosul Regulating Reservoir, North Iraq Using Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Thair M. Al-Taiee

    2013-05-01

    Full Text Available To obtain optimal operating rules for storage reservoirs, large numbers of simulation and optimization models have been developed over the past several decades, which vary significantly in their mechanisms and applications. Rule curves are guidelines for long term reservoir operation. An efficient technique is required to find the optimal rule curves that can mitigate water shortage in long term operation. The investigation of developed Genetic Algorithm (GA technique, which is an optimization approach base on the mechanics of natural selection, derived from the theory of natural evolution, was carried out to through the application to predict the daily rule curve of  Mosul regulating reservoir in Iraq.  Record daily inflows, outflow, water level in the reservoir for 19 year (1986-1990 and (1994-2007 were used in the developed model for assessing the optimal reservoir operation. The objective function is set to minimize the annual sum of squared deviation from the desired downstream release and desired storage volume in the reservoir. The decision variables are releases, storage volume, water level and outlet (demand from the reservoir. The results of the GA model gave a good agreement during the comparison with the actual rule curve and the designed rating curve of the reservoir. The simulated result shows that GA-derived policies are promising and competitive and can be effectively used for daily reservoir operation in addition to the rational monthly operation and predicting also rating curve of reservoirs.

  10. Influence of Chemical, Mechanical, and Transport Processes on Wellbore Leakage from Geologic CO2 Storage Reservoirs.

    Science.gov (United States)

    Carroll, Susan A; Iyer, Jaisree; Walsh, Stuart D C

    2017-08-15

    Wells are considered to be high-risk pathways for fluid leakage from geologic CO 2 storage reservoirs, because breaches in this engineered system have the potential to connect the reservoir to groundwater resources and the atmosphere. Given these concerns, a few studies have assessed leakage risk by evaluating regulatory records, often self-reported, documenting leakage in gas fields. Leakage is thought to be governed largely by initial well-construction quality and the method of well abandonment. The geologic carbon storage community has raised further concerns because acidic fluids in the CO 2 storage reservoir, alkaline cement meant to isolate the reservoir fluids from the overlying strata, and steel casings in wells are inherently reactive systems. This is of particular concern for storage of CO 2 in depleted oil and gas reservoirs with numerous legacy wells engineered to variable standards. Research suggests that leakage risks are not as great as initially perceived because chemical and mechanical alteration of cement has the capacity to seal damaged zones. Our work centers on defining the coupled chemical and mechanical processes governing flow in damaged zones in wells. We have developed process-based models, constrained by experiments, to better understand and forecast leakage risk. Leakage pathways can be sealed by precipitation of carbonate minerals in the fractures and deformation of the reacted cement. High reactivity of cement hydroxides releases excess calcium that can precipitate as carbonate solids in the fracture network under low brine flow rates. If the flow is fast, then the brine remains undersaturated with respect to the solubility of calcium carbonate minerals, and zones depleted in calcium hydroxides, enriched in calcium carbonate precipitates, and made of amorphous silicates leached of original cement minerals are formed. Under confining pressure, the reacted cement is compressed, which reduces permeability and lowers leakage risks. The

  11. Assessment of storm forecast

    DEFF Research Database (Denmark)

    Cutululis, Nicolaos Antonio; Hahmann, Andrea N.; Huus Bjerge, Martin

    When wind speed exceeds a certain value, wind turbines shut-down in order to protect their structure. This leads to sudden wind plants shut down and to new challenges concerning the secure operation of the pan-European electric system with future large scale offshore wind power. This task aims...... stopped, completely or partially, producing due to extreme wind speeds. Wind speed and power measurements from those events are presented and compared to the forecast available at Energinet.dk. The analysis looked at wind speed and wind power forecast. The main conclusion of the analysis is that the wind...... to consider it an EWP) and that the available wind speed forecasts are given as a mean wind speed over a rather large area. At wind power level, the analysis shows that prediction of accurate production levels from a wind farm experiencing EWP is rather poor. This is partially because the power curve...

  12. Financial Analysts’ Forecasts

    DEFF Research Database (Denmark)

    Stæhr, Simone

    . The primary focus is on financial analysts in the task of conducting earnings forecasts while a secondary focus is on investors’ abilities to interpret and make use of these forecasts. Simply put, financial analysts can be seen as information intermediators receiving inputs to their analyses from firm...... in the decision making and the magnitude of these constraints does sometimes vary with personal traits. Therefore, to the extent that financial analysts are subjects to behavioral biases their outputs to the investors are likely to be biased by their interpretation of information. Because investors need accuracy...... management and providing outputs to the investors. Amongst various outputs from the analysts are forecasts of earnings. According to decision theories mostly from the literature in psychology all humans are affected by cognitive constraints to some degree. These constraints may lead to unintentional biases...

  13. Wind power forecast

    Energy Technology Data Exchange (ETDEWEB)

    Pestana, Rui [Rede Electrica Nacional (REN), S.A., Lisboa (Portugal). Dept. Systems and Development System Operator; Trancoso, Ana Rosa; Delgado Domingos, Jose [Univ. Tecnica de Lisboa (Portugal). Seccao de Ambiente e Energia

    2012-07-01

    Accurate wind power forecast are needed to reduce integration costs in the electric grid caused by wind inherent variability. Currently, Portugal has a significant wind power penetration level and consequently the need to have reliable wind power forecasts at different temporal scales, including localized events such as ramps. This paper provides an overview of the methodologies used by REN to forecast wind power at national level, based on statistical and probabilistic combinations of NWP and measured data with the aim of improving accuracy of pure NWP. Results show that significant improvement can be achieved with statistical combination with persistence in the short-term and with probabilistic combination in the medium-term. NWP are also able to detect ramp events with 3 day notice to the operational planning. (orig.)

  14. Applicability of WRF-Lake System in Studying Reservoir-Induced Impacts on Local Climate: Case Study of Two Reservoirs with Contrasting Characteristics

    Science.gov (United States)

    Wang, F.; Zhu, D.; Ni, G.; Sun, T.

    2017-12-01

    Large reservoirs play a key role in regional hydrological cycles as well as in modulating the local climate. The emerging large reservoirs in concomitant with rapid hydropower exploitation in southwestern China warrant better understanding of their impacts on local and regional climates. One of the crucial pathways through which reservoirs impact the climate is lake-atmospheric interaction. Although such interactions have been widely studied with numeric weather prediction (NWP) models, an outstanding limitation across various NWPs resides on the poor thermodynamic representation of lakes. The recent version of Weather Research and Forecasting (WRF) system has been equipped with a one-dimensional lake model to better represent the thermodynamics of large water body and has been shown to enhance the its predication skill in the lake-atmospheric interaction. In this study, we further explore the applicability of the WRF-Lake system in two reservoirs with contrasting characteristics: Miyun Reservoir with an average depth of 30 meters in North China Plain, and Nuozhadu Reservoir with an average depth of 200 meters in the Tibetan Plateau Region. Driven by the high spatiotemporal resolution meteorological forcing data, the WRF-Lake system is used to simulate the water temperature and surface energy budgets of the two reservoirs after the evaluation against temperature observations. The simulated results show the WRF-Lake model can well predict the vertical profile of water temperature in Miyun Reservoir, but underestimates deep water temperature and overestimates surface temperature in the deeper Nuozhadu Reservoir. In addition, sensitivity analysis indicates the poor performance of the WRF-Lake system in Nuozhadu Reservoir could be attributed to the weak vertical mixing in the model, which can be improved by tuning the eddy diffusion coefficient ke . Keywords: reservoir-induced climatic impact; lake-atmospheric interaction; WRF-Lake system; hydropower exploitation

  15. Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

    Energy Technology Data Exchange (ETDEWEB)

    Hitzman, D.O.; Stepp, A.K.

    2003-02-11

    This research program was directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal was to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with inorganic nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil-releasing agents. The potential of the system will be illustrated and demonstrated by the example of biopolymer production on oil recovery.

  16. Forecast of auroral activity

    International Nuclear Information System (INIS)

    Lui, A.T.Y.

    2004-01-01

    A new technique is developed to predict auroral activity based on a sample of over 9000 auroral sites identified in global auroral images obtained by an ultraviolet imager on the NASA Polar satellite during a 6-month period. Four attributes of auroral activity sites are utilized in forecasting, namely, the area, the power, and the rates of change in area and power. This new technique is quite accurate, as indicated by the high true skill scores for forecasting three different levels of auroral dissipation during the activity lifetime. The corresponding advanced warning time ranges from 22 to 79 min from low to high dissipation levels

  17. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

    Davis, Neil; Hahmann, Andrea N.; Clausen, Niels-Erik

    2012-01-01

    In this study, we present a method for forecasting icing events. The method is validated at two European wind farms in with known icing events. The icing model used was developed using current ice accretion methods, and newly developed ablation algorithms. The model is driven by inputs from the WRF...... mesoscale model, allowing for both climatological estimates of icing and short term icing forecasts. The current model was able to detect periods of icing reasonably well at the warmer site. However at the cold climate site, the model was not able to remove ice quickly enough leading to large ice...

  18. Spatial load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Willis, H.L.; Engel, M.V.; Buri, M.J.

    1995-04-01

    The reliability, efficiency, and economy of a power delivery system depend mainly on how well its substations, transmission lines, and distribution feeders are located within the utility service area, and how well their capacities match power needs in their respective localities. Often, utility planners are forced to commit to sites, rights of way, and equipment capacities year in advance. A necessary element of effective expansion planning is a forecast of where and how much demand must be served by the future T and D system. This article reports that a three-stage method forecasts with accuracy and detail, allowing meaningful determination of sties and sizes for future substation, transmission, and distribution facilities.

  19. Forecasting Housing Approvals in Australia: Do Forecasters Herd?

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Rülke

    2012-01-01

    Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find...

  20. Tsengwen Reservoir Watershed Hydrological Flood Simulation Under Global Climate Change Using the 20 km Mesh Meteorological Research Institute Atmospheric General Circulation Model (MRI-AGCM

    Directory of Open Access Journals (Sweden)

    Nobuaki Kimura

    2014-01-01

    Full Text Available Severe rainstorms have occurred more frequently in Taiwan over the last decade. To understand the flood characteristics of a local region under climate change, a hydrological model simulation was conducted for the Tsengwen Reservoir watershed. The model employed was the Integrated Flood Analysis System (IFAS, which has a conceptual, distributed rainfall-runoff analysis module and a GIS data-input function. The high-resolution rainfall data for flood simulation was categorized into three terms: 1979 - 2003 (Present, 2015 - 2039 (Near-future, and 2075 - 2099 (Future, provided by the Meteorological Research Institute atmospheric general circulation model (MRI-AGCM. Ten extreme rainfall (top ten events were selected for each term in descending order of total precipitation volume. Due to the small watershed area the MRI-AGCM3.2S data was downsized into higher resolution data using the Weather Research and Forecasting Model. The simulated discharges revealed that most of the Near-future and Future peaks caused by extreme rainfall increased compared to the Present peak. These ratios were 0.8 - 1.6 (Near-future/Present and 0.9 - 2.2 (Future/Present, respectively. Additionally, we evaluated how these future discharges would affect the reservoir¡¦s flood control capacity, specifically the excess water volume required to be stored while maintaining dam releases up to the dam¡¦s spillway capacity or the discharge peak design for flood prevention. The results for the top ten events show that the excess water for the Future term exceeded the reservoir¡¦s flood control capacity and was approximately 79.6 - 87.5% of the total reservoir maximum capacity for the discharge peak design scenario.

  1. A unique application of the instream flow incremental methodology (IFIM) to predict impacts on riverine aquatic habitat, resulting from construction of a proposed hydropower reservoir

    International Nuclear Information System (INIS)

    Foote, P.S.

    1999-01-01

    The City of Harrisburg, Pennsylvania, proposed to construct a new low-head hydroelectric project on the Susquehanna River in the central part of the state in 1986, about 108 km upstream of the river mouth. As part of the licensing process, the city was required by the Federal Energy Regulatory Commission to carry out studies that would forecast the impacts on riverine aquatic habitat as a result of construction of the proposed 13 km long by 1.5 km wide reservoir. The methodology selected by the city and its consultants was to use the IFIM to model the habitat conditions in the project reach both before and after construction of the proposed reservoir.The IFIM is usually used to model instream flow releases downstream of dams and diversions, and had not been used before to model habitat conditions within the proposed reservoir area. The study team hydraulically modelled the project reach using existing hydraulic data, and a HEC-2 backwater analysis to determine post-project water surface elevations. The IFG-4 model was used to simulate both pre- and post-project water velocities, by distributing velocities across transects based on known discharges and cell depth. Effects on aquatic habitat were determined using the IFIM PHABSIM program, in which criteria for several evaluation species and life stages were used to yield estimates of Weighted Usable Area. The analysis showed, based on trends in WUA from pre- and post-project conditions, that habitat conditions would improve for several species and life stages, and would be negatively affected for fewer life stages and species. Some agency concerns that construction of the proposed reservoir would have significant adverse effects on the resident and anadromous fish populations were responded to using these results

  2. Pollutant forecasting error based on persistence of wind direction

    International Nuclear Information System (INIS)

    Cooper, R.E.

    1978-01-01

    The purpose of this report is to provide a means of estimating the reliability of forecasts of downwind pollutant concentrations from atmospheric puff releases. These forecasts are based on assuming the persistence of wind direction as determined at the time of release. This initial forecast will be used to deploy survey teams, to predict population centers that may be affected, and to estimate the amount of time available for emergency response. Reliability of forecasting is evaluated by developing a cumulative probability distribution of error as a function of lapsed time following an assumed release. The cumulative error is determined by comparing the forecast pollutant concentration with the concentration measured by sampling along the real-time meteorological trajectory. It may be concluded that the assumption of meteorological persistence for emergency response is not very good for periods longer than 3 hours. Even within this period, the possibiity for large error exists due to wind direction shifts. These shifts could affect population areas totally different from those areas first indicated

  3. CDM Convective Forecast Planning guidance

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The CDM Convective Forecast Planning (CCFP) guidance product provides a foreast of en-route aviation convective hazards. The forecasts are updated every 2 hours and...

  4. Are demand forecasting techniques applicable to libraries?

    OpenAIRE

    Sridhar, M. S.

    1984-01-01

    Examines the nature and limitations of demand forecasting, discuses plausible methods of forecasting demand for information, suggests some useful hints for demand forecasting and concludes by emphasizing unified approach to demand forecasting.

  5. Comparison of Strategies for Climate Change Adaptation of Water Supply and Flood Control Reservoirs

    Science.gov (United States)

    Ng, T. L.; Yang, P.; Bhushan, R.

    2016-12-01

    With climate change, streamflows are expected to become more fluctuating, with more frequent and intense floods and droughts. This complicates reservoir operation, which is highly sensitive to inflow variability. We make a comparative evaluation of three strategies for adapting reservoirs to climate-induced shifts in streamflow patterns. Specifically, we examine the effectiveness of (i) expanding the capacities of reservoirs by way of new off-stream reservoirs, (ii) introducing wastewater reclamation to augment supplies, and (iii) improving real-time streamflow forecasts for more optimal decision-making. The first two are hard strategies involving major infrastructure modifications, while the third a soft strategy entailing adjusting the system operation. A comprehensive side-by-side comparison of the three strategies is as yet lacking in the literature despite the many past studies investigating the strategies individually. To this end, we developed an adaptive forward-looking linear program that solves to yield the optimal decisions for the current time as a function of an ensemble forecast of future streamflows. Solving the model repeatedly on a rolling basis with regular updating of the streamflow forecast simulates the system behavior over the entire operating horizon. Results are generated for two hypothetical water supply and flood control reservoirs of differing inflows and demands. Preliminary findings suggest that of the three strategies, improving streamflow forecasts to be most effective in mitigating the effects of climate change. We also found that, in average terms, both additional reservoir capacity and wastewater reclamation have potential to reduce water shortage and downstream flooding. However, in the worst case, the potential of the former to reduce water shortage is limited, and similarly so the potential of the latter to reduce downstream flooding.

  6. A Step Forward to Closing the Loop between Static and Dynamic Reservoir Modeling

    Directory of Open Access Journals (Sweden)

    Cancelliere M.

    2014-12-01

    Full Text Available The current trend for history matching is to find multiple calibrated models instead of a single set of model parameters that match the historical data. The advantage of several current workflows involving assisted history matching techniques, particularly those based on heuristic optimizers or direct search, is that they lead to a number of calibrated models that partially address the problem of the non-uniqueness of the solutions. The importance of achieving multiple solutions is that calibrated models can be used for a true quantification of the uncertainty affecting the production forecasts, which represent the basis for technical and economic risk analysis. In this paper, the importance of incorporating the geological uncertainties in a reservoir study is demonstrated. A workflow, which includes the analysis of the uncertainty associated with the facies distribution for a fluvial depositional environment in the calibration of the numerical dynamic models and, consequently, in the production forecast, is presented. The first step in the workflow was to generate a set of facies realizations starting from different conceptual models. After facies modeling, the petrophysical properties were assigned to the simulation domains. Then, each facies realization was calibrated separately by varying permeability and porosity fields. Data assimilation techniques were used to calibrate the models in a reasonable span of time. Results showed that even the adoption of a conceptual model for facies distribution clearly representative of the reservoir internal geometry might not guarantee reliable results in terms of production forecast. Furthermore, results also showed that realizations which seem fully acceptable after calibration were not representative of the true reservoir internal configuration and provided wrong production forecasts; conversely, realizations which did not show a good fit of the production data could reliably predict the reservoir

  7. Design of a lube oil reservoir by using flow calculations

    Energy Technology Data Exchange (ETDEWEB)

    Rinkinen, J; Alfthan, A. [Institute of Hydraulics and Automation IHA, Tampere University of Technology, Tampere (Finland)] Suominen, J. [Institute of Energy and Process Engineering, Tampere University of Technology, Tampere (Finland); Airaksinen, A; Antila, K [R and D Engineer Safematic Oy, Muurame (Finland)

    1998-12-31

    The volume of usual oil reservoir for lubrication oil systems is designed by the traditional rule of thumb so that the total oil volume is theoretically changed in every 30 minutes by rated pumping capacity. This is commonly used settling time for air, water and particles to separate by gravity from the oil returning of the bearings. This leads to rather big volumes of lube oil reservoirs, which are sometimes difficult to situate in different applications. In this presentation traditionally sized lube oil reservoir (8 m{sup 3}) is modelled in rectangular coordinates and laminar oil flow is calculated by using FLUENT software that is based on finite difference method. The results of calculation are velocity and temperature fields inside the reservoir. The velocity field is used to visualize different particle paths through the reservoir. Particles that are studied by the model are air bubbles and water droplets. The interest of the study has been to define the size of the air bubbles that are released and the size of the water droplets that are separated in the reservoir. The velocity field is also used to calculate the modelled circulating time of the oil volume which is then compared with the theoretical circulating time that is obtained from the rated pump flow. These results have been used for designing a new lube oil reservoir. This reservoir has also been modelled and optimized by the aid of flow calculations. The best shape of the designed reservoir is constructed in real size for empirical measurements. Some results of the oil flow measurements are shown. (orig.) 7 refs.

  8. Design of a lube oil reservoir by using flow calculations

    Energy Technology Data Exchange (ETDEWEB)

    Rinkinen, J.; Alfthan, A. [Institute of Hydraulics and Automation IHA, Tampere University of Technology, Tampere (Finland)] Suominen, J. [Institute of Energy and Process Engineering, Tampere University of Technology, Tampere (Finland); Airaksinen, A.; Antila, K. [R and D Engineer Safematic Oy, Muurame (Finland)

    1997-12-31

    The volume of usual oil reservoir for lubrication oil systems is designed by the traditional rule of thumb so that the total oil volume is theoretically changed in every 30 minutes by rated pumping capacity. This is commonly used settling time for air, water and particles to separate by gravity from the oil returning of the bearings. This leads to rather big volumes of lube oil reservoirs, which are sometimes difficult to situate in different applications. In this presentation traditionally sized lube oil reservoir (8 m{sup 3}) is modelled in rectangular coordinates and laminar oil flow is calculated by using FLUENT software that is based on finite difference method. The results of calculation are velocity and temperature fields inside the reservoir. The velocity field is used to visualize different particle paths through the reservoir. Particles that are studied by the model are air bubbles and water droplets. The interest of the study has been to define the size of the air bubbles that are released and the size of the water droplets that are separated in the reservoir. The velocity field is also used to calculate the modelled circulating time of the oil volume which is then compared with the theoretical circulating time that is obtained from the rated pump flow. These results have been used for designing a new lube oil reservoir. This reservoir has also been modelled and optimized by the aid of flow calculations. The best shape of the designed reservoir is constructed in real size for empirical measurements. Some results of the oil flow measurements are shown. (orig.) 7 refs.

  9. The management of subsurface uncertainty using probabilistic modeling of life cycle production forecasts and cash flows

    International Nuclear Information System (INIS)

    Olatunbosun, O. O.

    1998-01-01

    The subject pertains to the implementation of the full range of subsurface uncertainties in life cycle probabilistic forecasting and its extension to project cash flows using the methodology of probabilities. A new tool has been developed in the probabilistic application of Crystal-Ball which can model reservoir volumetrics, life cycle production forecasts and project cash flows in a single environment. The tool is modular such that the volumetrics and cash flow modules are optional. Production forecasts are often generated by applying a decline equation to single best estimate values of input parameters such as initial potential, decline rate, abandonment rate etc -or sometimes by results of reservoir simulation. This new tool provides a means of implementing the full range of uncertainties and interdependencies of the input parameters into the production forecasts by defining the input parameters as probability density functions, PDFs and performing several iterations to generate an expectation curve forecast. Abandonment rate is implemented in each iteration via a link to an OPEX model. The expectation curve forecast is input into a cash flow model to generate a probabilistic NPV. Base case and sensitivity runs from reservoir simulation can likewise form the basis for a probabilistic production forecast from which a probabilistic cash flow can be generated. A good illustration of the application of this tool is in the modelling of the production forecast for a well that encounters its target reservoirs in OUT/ODT situation and thus has significant uncertainties. The uncertainty in presence and size (if present) of gas cap and dependency between ultimate recovery and initial potential amongst other uncertainties can be easily implemented in the production forecast with this tool. From the expectation curve forecast, a probabilistic NPV can be easily generated. Possible applications of this tool include: i. estimation of range of actual recoverable volumes based

  10. Forecasting of superconducting compounds

    International Nuclear Information System (INIS)

    Savitskii, E.M.; Gribulya, V.G.; Kiseleva, N.N.

    1981-01-01

    In forecasting new superconducting intermetallic compounds of the A15 and Mo 3 Se types most promising from the viewpoint of high critical temperature Tsub(c), high critical magnetic fields Hsub(c), and high critical currents and in estimating their transition temperature it is proposed to apply cybernetic methods of computer learning

  11. Forecast of nuclear energetics

    Energy Technology Data Exchange (ETDEWEB)

    Sikora, W

    1976-01-01

    The forecast concerning the development of nuclear energetics is presented. Some information on economics of nuclear power plants is given. The nuclear fuel reserves are estimated on the background of power resources of the world. The safety and environment protection problems are mentioned.

  12. Climate Forecast System

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Forecast System Home News Organization Web portal to all Federal, state and local government Web resources and services. The NCEP Climate when using the CFS Reanalysis (CFSR) data. Saha, Suranjana, and Coauthors, 2010: The NCEP Climate

  13. Foresight and Forecasts

    DEFF Research Database (Denmark)

    Kilbourn, Kyle; Bay, Marie Brøndum

    In predicting areas of growth, public innovation projects may rely on optimistic visions of technology still in development as a way of ensuring novelty for funding. This paper explores what happens when forecasts of robotic technology meets the practice of sterile supply in a preliminary stage...

  14. Hydrology and flow forecasting

    NARCIS (Netherlands)

    Vrijling, J.K.; Kwadijk, J.; Van Duivendijk, J.; Van Gelder, P.; Pang, H.; Rao, S.Q.; Wang, G.Q.; Huang, X.Q.

    2002-01-01

    We have studied and applied the statistic model (i.e. MMC) and hydrological models to Upper Yellow River. This report introduces the results and some conclusions from the model. The three models, MMC, MWBM and NAM, have be applied in the research area. The forecasted discharge by the three models

  15. NWS Marine Forecast Areas

    Science.gov (United States)

    of Commerce Ocean Prediction Center National Oceanic and Atmospheric Administration Analysis & Unified Surface Analysis Ocean Ocean Products Ice & Icebergs NIC Ice Products NAIS Iceberg Analysis Social Media Facebook Twitter YouTube Search Search For Go NWS All NOAA NWS Marine Forecast Areas

  16. The Latest Forecast.

    Science.gov (United States)

    Laurence, David

    2002-01-01

    Discusses the "latest forecast" for the future of English departments. Addresses departmental and institutional staffing practices, employment opportunities for PhDs, the acceleration of change in the institution, and the general state of the study and teaching of English. (RS)

  17. Ecological forecasts: An emerging imperative

    Science.gov (United States)

    James S. Clark; Steven R. Carpenter; Mary Barber; Scott Collins; Andy Dobson; Jonathan A. Foley; David M. Lodge; Mercedes Pascual; Roger Pielke; William Pizer; Cathy Pringle; Walter V. Reid; Kenneth A. Rose; Osvaldo Sala; William H. Schlesinger; Diana H. Wall; David Wear

    2001-01-01

    Planning and decision-making can be improved by access to reliable forecasts of ecosystem state, ecosystem services, and natural capital. Availability of new data sets, together with progress in computation and statistics, will increase our ability to forecast ecosystem change. An agenda that would lead toward a capacity to produce, evaluate, and communicate forecasts...

  18. Air Pollution Forecasts: An Overview

    Science.gov (United States)

    Bai, Lu; Wang, Jianzhou; Lu, Haiyan

    2018-01-01

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies. PMID:29673227

  19. Air Pollution Forecasts: An Overview.

    Science.gov (United States)

    Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

    2018-04-17

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  20. Air Pollution Forecasts: An Overview

    Directory of Open Access Journals (Sweden)

    Lu Bai

    2018-04-01

    Full Text Available Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  1. Storm Prediction Center Forecast Products

    Science.gov (United States)

    select the go button to submit request Local forecast by "City, St" or "ZIP" City, St Archive NOAA Weather Radio Research Non-op. Products Forecast Tools Svr. Tstm. Events SPC Publications SPC services. Forecast Products Current Weather Watches This is the current graphic showing any severe

  2. Advances in photonic reservoir computing

    Science.gov (United States)

    Van der Sande, Guy; Brunner, Daniel; Soriano, Miguel C.

    2017-05-01

    We review a novel paradigm that has emerged in analogue neuromorphic optical computing. The goal is to implement a reservoir computer in optics, where information is encoded in the intensity and phase of the optical field. Reservoir computing is a bio-inspired approach especially suited for processing time-dependent information. The reservoir's complex and high-dimensional transient response to the input signal is capable of universal computation. The reservoir does not need to be trained, which makes it very well suited for optics. As such, much of the promise of photonic reservoirs lies in their minimal hardware requirements, a tremendous advantage over other hardware-intensive neural network models. We review the two main approaches to optical reservoir computing: networks implemented with multiple discrete optical nodes and the continuous system of a single nonlinear device coupled to delayed feedback.

  3. Encapsulated microsensors for reservoir interrogation

    Science.gov (United States)

    Scott, Eddie Elmer; Aines, Roger D.; Spadaccini, Christopher M.

    2016-03-08

    In one general embodiment, a system includes at least one microsensor configured to detect one or more conditions of a fluidic medium of a reservoir; and a receptacle, wherein the receptacle encapsulates the at least one microsensor. In another general embodiment, a method include injecting the encapsulated at least one microsensor as recited above into a fluidic medium of a reservoir; and detecting one or more conditions of the fluidic medium of the reservoir.

  4. Comparison of random forests and support vector machine for real-time radar-derived rainfall forecasting

    Science.gov (United States)

    Yu, Pao-Shan; Yang, Tao-Chang; Chen, Szu-Yin; Kuo, Chen-Min; Tseng, Hung-Wei

    2017-09-01

    This study aims to compare two machine learning techniques, random forests (RF) and support vector machine (SVM), for real-time radar-derived rainfall forecasting. The real-time radar-derived rainfall forecasting models use the present grid-based radar-derived rainfall as the output variable and use antecedent grid-based radar-derived rainfall, grid position (longitude and latitude) and elevation as the input variables to forecast 1- to 3-h ahead rainfalls for all grids in a catchment. Grid-based radar-derived rainfalls of six typhoon events during 2012-2015 in three reservoir catchments of Taiwan are collected for model training and verifying. Two kinds of forecasting models are constructed and compared, which are single-mode forecasting model (SMFM) and multiple-mode forecasting model (MMFM) based on RF and SVM. The SMFM uses the same model for 1- to 3-h ahead rainfall forecasting; the MMFM uses three different models for 1- to 3-h ahead forecasting. According to forecasting performances, it reveals that the SMFMs give better performances than MMFMs and both SVM-based and RF-based SMFMs show satisfactory performances for 1-h ahead forecasting. However, for 2- and 3-h ahead forecasting, it is found that the RF-based SMFM underestimates the observed radar-derived rainfalls in most cases and the SVM-based SMFM can give better performances than RF-based SMFM.

  5. Evaluations of Extended-Range tropical Cyclone Forecasts in the Western North Pacific by using the Ensemble Reforecasts: Preliminary Results

    Science.gov (United States)

    Tsai, Hsiao-Chung; Chen, Pang-Cheng; Elsberry, Russell L.

    2017-04-01

    The objective of this study is to evaluate the predictability of the extended-range forecasts of tropical cyclone (TC) in the western North Pacific using reforecasts from National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS) during 1996-2015, and from the Climate Forecast System (CFS) during 1999-2010. Tsai and Elsberry have demonstrated that an opportunity exists to support hydrological operations by using the extended-range TC formation and track forecasts in the western North Pacific from the ECMWF 32-day ensemble. To demonstrate this potential for the decision-making processes regarding water resource management and hydrological operation in Taiwan reservoir watershed areas, special attention is given to the skill of the NCEP GEFS and CFS models in predicting the TCs affecting the Taiwan area. The first objective of this study is to analyze the skill of NCEP GEFS and CFS TC forecasts and quantify the forecast uncertainties via verifications of categorical binary forecasts and probabilistic forecasts. The second objective is to investigate the relationships among the large-scale environmental factors [e.g., El Niño Southern Oscillation (ENSO), Madden-Julian Oscillation (MJO), etc.] and the model forecast errors by using the reforecasts. Preliminary results are indicating that the skill of the TC activity forecasts based on the raw forecasts can be further improved if the model biases are minimized by utilizing these reforecasts.

  6. modeling of modeling of reservoir in reservoir in artificial neu

    African Journals Online (AJOL)

    eobe

    adequate inflow data modeling and forecasting is v essential for proper ... eed correct measurement, ates for future planning and .... (CCANN) were used to evaluate performance of ANNs in estimating ... appropriate low flow forecast model for the Meuse. River in Netherlands based on the comparison of output uncertainties ...

  7. All-optical reservoir computing.

    Science.gov (United States)

    Duport, François; Schneider, Bendix; Smerieri, Anteo; Haelterman, Marc; Massar, Serge

    2012-09-24

    Reservoir Computing is a novel computing paradigm that uses a nonlinear recurrent dynamical system to carry out information processing. Recent electronic and optoelectronic Reservoir Computers based on an architecture with a single nonlinear node and a delay loop have shown performance on standardized tasks comparable to state-of-the-art digital implementations. Here we report an all-optical implementation of a Reservoir Computer, made of off-the-shelf components for optical telecommunications. It uses the saturation of a semiconductor optical amplifier as nonlinearity. The present work shows that, within the Reservoir Computing paradigm, all-optical computing with state-of-the-art performance is possible.

  8. Effects of reservoirs water level variations on fish recruitment

    Directory of Open Access Journals (Sweden)

    Fabíula T. de Lima

    2017-10-01

    Full Text Available ABSTRACT The construction of hydroelectric power plants has many social and environmental impacts. Among them, the impacts on fish communities, which habitats are drastically modified by dams, with consequences across the ecosystem. This study aimed to assess the influence of water level (WL variations in the reservoirs of the Itá and Machadinho hydroelectric plants on the recruitment of fish species from the upper Uruguay River in southern Brazil. The data analyzed resulted from the WL variation produced exclusively by the hydroelectric plants generation and were collected between the years 2001 and 2012. The results showed significant correlations between the abundance of juvenile fish and the hydrological parameters only for some reproductive guilds. The species that spawn in nests showed, in general, a clear preference for the stability in the WL of the reservoirs, while the species that spawn in macrophytes or that release demersal eggs showed no significant correlation between the abundance of juvenile fish and hydrological parameters. A divergence of results between the two reservoirs was observed between the species that release semi-dense eggs; a positive correlation with a more stable WL was only observed in the Machadinho reservoir. This result can be driven by a wider range of WL variation in Machadinho reservoir.

  9. Numerical Weather Forecasting at the Savannah River Site

    International Nuclear Information System (INIS)

    Buckley, R.L.

    1999-01-01

    Facilities such as the Savannah River Site (SRS), which contain the potential for hazardous atmospheric releases, rely on the predictive capabilities of dispersion models to assess possible emergency response actions. The operational design in relation to domain size and forecast time is presented, along with verification of model results over extended time periods with archived surface observations

  10. Integrated Flood Forecast and Virtual Dam Operation System for Water Resources and Flood Risk Management

    Science.gov (United States)

    Shibuo, Yoshihiro; Ikoma, Eiji; Lawford, Peter; Oyanagi, Misa; Kanauchi, Shizu; Koudelova, Petra; Kitsuregawa, Masaru; Koike, Toshio

    2014-05-01

    While availability of hydrological- and hydrometeorological data shows growing tendency and advanced modeling techniques are emerging, such newly available data and advanced models may not always be applied in the field of decision-making. In this study we present an integrated system of ensemble streamflow forecast (ESP) and virtual dam simulator, which is designed to support river and dam manager's decision making. The system consists of three main functions: real time hydrological model, ESP model, and dam simulator model. In the real time model, the system simulates current condition of river basins, such as soil moisture and river discharges, using LSM coupled distributed hydrological model. The ESP model takes initial condition from the real time model's output and generates ESP, based on numerical weather prediction. The dam simulator model provides virtual dam operation and users can experience impact of dam control on remaining reservoir volume and downstream flood under the anticipated flood forecast. Thus the river and dam managers shall be able to evaluate benefit of priori dam release and flood risk reduction at the same time, on real time basis. Furthermore the system has been developed under the concept of data and models integration, and it is coupled with Data Integration and Analysis System (DIAS) - a Japanese national project for integrating and analyzing massive amount of observational and model data. Therefore it has advantage in direct use of miscellaneous data from point/radar-derived observation, numerical weather prediction output, to satellite imagery stored in data archive. Output of the system is accessible over the web interface, making information available with relative ease, e.g. from ordinary PC to mobile devices. We have been applying the system to the Upper Tone region, located northwest from Tokyo metropolitan area, and we show application example of the system in recent flood events caused by typhoons.

  11. Multi-data reservoir history matching of crosswell seismic, electromagnetics and gravimetry data

    KAUST Repository

    Katterbauer, Klemens

    2014-01-01

    Reservoir engineering has become of prime importance for oil and gas field development projects. With rising complexity, reservoir simulations and history matching have become critical for fine-tuning reservoir production strategies, improved subsurface formation knowledge and forecasting remaining reserves. The sparse spatial sampling of production data has posed a significant challenge for reducing uncertainty of subsurface parameters. Seismic, electromagnetic and gravimetry techniques have found widespread application in enhancing exploration for oil and gas and monitor reservoirs, however these data have been interpreted and analyzed mostly separately rarely utilizing the synergy effects that may be attainable. With the incorporation of multiple data into the reservoir history matching process there has been the request knowing the impact each incorporated observation has on the estimation. We present multi-data ensemble-based history matching framework for the incorporation of multiple data such as seismic, electromagnetics, and gravimetry for improved reservoir history matching and provide an adjointfree ensemble sensitivity method to compute the impact of each observation on the estimated reservoir parameters. The incorporation of all data sets displays the advantages multiple data may provide for enhancing reservoir understanding and matching, with the impact of each data set on the matching improvement being determined by the ensemble sensitivity method.

  12. The Potential of a Surfactant/Polymer Flood in a Middle Eastern Reservoir

    Directory of Open Access Journals (Sweden)

    Meshal Algharaib

    2012-01-01

    Full Text Available An integrated full-field reservoir simulation study has been performed to determine the reservoir management and production strategies in a mature sandstone reservoir. The reservoir is a candidate for an enhanced oil recovery process or otherwise subject to abandonment. Based on its charateristics, the reservoir was found to be most suited for a surfactant/polymer (SP flood. The study started with a large data gathering and the building of a full-field three-dimensional geological model. Subsequently, a full field simulation model was built and used to history match the water flood. The history match of the water flood emphasizes the areas with remaining high oil saturations, establishes the initial condition of the reservoir for an SP flood, and generates a forecast of reserves for continued water flood operations. A sector model was constructed from the full field model and then used to study different design parameters to maximize the project profitability from the SP flood. An economic model, based on the estimated recovery, residual oil in-place, oil price, and operating costs, has been implemented in order to optimize the project profitability. The study resulted in the selection of surfactant and polymer concentrations and slug size that yielded the best economic returns when applied in this reservoir. The study shows that, in today’s oil prices, surfactant/polymer flood when applied in this reservoir has increased the ultimate oil recovery and provide a significant financial returns.

  13. Load forecasting for supermarket refrigeration

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Aalborg Nielsen, Henrik

    This report presents a study of models for forecasting the load for supermarket refrigeration. The data used for building the forecasting models consists of load measurements, local climate measurements and weather forecasts. The load measurements are from a supermarket located in a village...... in Denmark. The load for refrigeration is the sum of all cabinets in the supermarket, both low and medium temperature cabinets, and spans a period of one year. As input to the forecasting models the ambient temperature observed near the supermarket together with weather forecasts are used. Every hour...

  14. Evaluation Of Statistical Models For Forecast Errors From The HBV-Model

    Science.gov (United States)

    Engeland, K.; Kolberg, S.; Renard, B.; Stensland, I.

    2009-04-01

    Three statistical models for the forecast errors for inflow to the Langvatn reservoir in Northern Norway have been constructed and tested according to how well the distribution and median values of the forecasts errors fit to the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order autoregressive model was constructed for the forecast errors. The parameters were conditioned on climatic conditions. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order autoregressive model was constructed for the forecast errors. For the last model positive and negative errors were modeled separately. The errors were first NQT-transformed before a model where the mean values were conditioned on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: We wanted a) the median values to be close to the observed values; b) the forecast intervals to be narrow; c) the distribution to be correct. The results showed that it is difficult to obtain a correct model for the forecast errors, and that the main challenge is to account for the auto-correlation in the errors. Model 1 and 2 gave similar results, and the main drawback is that the distributions are not correct. The 95% forecast intervals were well identified, but smaller forecast intervals were over-estimated, and larger intervals were under-estimated. Model 3 gave a distribution that fits better, but the median values do not fit well since the auto-correlation is not properly accounted for. If the 95% forecast interval is of interest, Model 2 is recommended. If the whole distribution is of interest, Model 3 is recommended.

  15. Future reservoir management under climate change for the Mississippi River

    International Nuclear Information System (INIS)

    Asnaashari, Ahmad; Gharabaghi, Bahram; McBean, Edward A.; Kunjikutty, Sobhalatha; Lehman, Paul; Wade, Winston

    2010-01-01

    This paper is part of an ongoing research project designed to evaluate the effect of climate change on reservoir operation policies in the Mississippi Valley Conservation Authority. The study used the results from a first paper, including projected daily temperature and precipitation, for future streamflow calculation. This paper presented the development, calibration and validation of a rainfall-runoff NAM model for the Mississippi River watershed. The calibrated Mike11/NAM model was fed with predicted climatic data to generate long term future streamflow in the basin. Forecast flows were run in a Mike 11/HD model to estimate the corresponding lake levels. The storages and flows at Shabomeka Lake, Mazinaw Lake and Marble Lake were simulated. The results showed that climate change is likely to have implications for reservoir operations in the Mississippi River watershed, which will include changed water level regimes due to modifications in the projected future streamflow hydrograph to meet desired lake levels.

  16. The mechanics of shallow magma reservoir outgassing

    Science.gov (United States)

    Parmigiani, A.; Degruyter, W.; Leclaire, S.; Huber, C.; Bachmann, O.

    2017-08-01

    Magma degassing fundamentally controls the Earth's volatile cycles. The large amount of gas expelled into the atmosphere during volcanic eruptions (i.e., volcanic outgassing) is the most obvious display of magmatic volatile release. However, owing to the large intrusive:extrusive ratio, and considering the paucity of volatiles left in intrusive rocks after final solidification, volcanic outgassing likely constitutes only a small fraction of the overall mass of magmatic volatiles released to the Earth's surface. Therefore, as most magmas stall on their way to the surface, outgassing of uneruptible, crystal-rich magma storage regions will play a dominant role in closing the balance of volatile element cycling between the mantle and the surface. We use a numerical approach to study the migration of a magmatic volatile phase (MVP) in crystal-rich magma bodies ("mush zones") at the pore scale. Our results suggest that buoyancy-driven outgassing is efficient over crystal volume fractions between 0.4 and 0.7 (for mm-sized crystals). We parameterize our pore-scale results for MVP migration in a thermomechanical magma reservoir model to study outgassing under dynamical conditions where cooling controls the evolution of the proportion of crystal, gas, and melt phases and to investigate the role of the reservoir size and the temperature-dependent viscoelastic response of the crust on outgassing efficiency. We find that buoyancy-driven outgassing allows for a maximum of 40-50% volatiles to leave the reservoir over the 0.4-0.7 crystal volume fractions, implying that a significant amount of outgassing must occur at high crystal content (>0.7) through veining and/or capillary fracturing.

  17. Sediment pollution characteristics and in situ control in a deep drinking water reservoir.

    Science.gov (United States)

    Zhou, Zizhen; Huang, Tinglin; Li, Yang; Ma, Weixing; Zhou, Shilei; Long, Shenghai

    2017-02-01

    Sediment pollution characteristics, in situ sediment release potential, and in situ inhibition of sediment release were investigated in a drinking water reservoir. Results showed that organic carbon (OC), total nitrogen (TN), and total phosphorus (TP) in sediments increased from the reservoir mouth to the main reservoir. Fraction analysis indicated that nitrogen in ion exchangeable form and NaOH-extractable P (Fe/Al-P) accounted for 43% and 26% of TN and TP in sediments of the main reservoir. The Risk Assessment Code for metal elements showed that Fe and Mn posed high to very high risk. The results of the in situ reactor experiment in the main reservoir showed the same trends as those observed in the natural state of the reservoir in 2011 and 2012; the maximum concentrations of total OC, TN, TP, Fe, and Mn reached 4.42mg/L, 3.33mg/L, 0.22mg/L, 2.56mg/L, and 0.61mg/L, respectively. An in situ sediment release inhibition technology, the water-lifting aerator, was utilized in the reservoir. The results of operating the water-lifting aerator indicated that sediment release was successfully inhibited and that OC, TN, TP, Fe, and Mn in surface sediment could be reduced by 13.25%, 15.23%, 14.10%, 5.32%, and 3.94%, respectively. Copyright © 2016. Published by Elsevier B.V.

  18. The use of various interplanetary scintillation indices within geomagnetic forecasts

    Directory of Open Access Journals (Sweden)

    E. A. Lucek

    Full Text Available Interplanetary scintillation (IPS, the twinkling of small angular diameter radio sources, is caused by the interaction of the signal with small-scale plasma irregularities in the solar wind. The technique may be used to sense remotely the near-Earth heliosphere and observations of a sufficiently large number of sources may be used to track large-scale disturbances as they propagate from close to the Sun to the Earth. Therefore, such observations have potential for use within geomagnetic forecasts. We use daily data from the Mullard Radio Astronomy Observatory, made available through the World Data Centre, to test the success of geomagnetic forecasts based on IPS observations. The approach discussed here was based on the reduction of the information in a map to a single number or series of numbers. The advantages of an index of this nature are that it may be produced routinely and that it could ideally forecast both the occurrence and intensity of geomagnetic activity. We start from an index that has already been described in the literature, INDEX35. On the basis of visual examination of the data in a full skymap format modifications were made to the way in which the index was calculated. It was hoped that these would lead to an improvement in its forecasting ability. Here we assess the forecasting potential of the index using the value of the correlation coefficient between daily Ap and the IPS index, with IPS leading by 1 day. We also compare the forecast based on the IPS index with forecasts of Ap currently released by the Space Environment Services Center (SESC. Although we find that the maximum improvement achieved is small, and does not represent a significant advance in forecasting ability, the IPS forecasts at this phase of the solar cycle are of a similar quality to those made by SESC.

  19. Cesium reservoir and interconnective components

    International Nuclear Information System (INIS)

    1994-03-01

    The program objective is to demonstrate the technology readiness of a TFE (thermionic fuel element) suitable for use as the basic element in a thermionic reactor with electric power output in the 0.5 to 5.0 MW range. A thermionic converter must be supplied with cesium vapor for two reasons. Cesium atoms adsorbed on the surface of the emitter cause a reduction of the emitter work function to permit high current densities without excessive heating of the emitter. The second purpose of the cesium vapor is to provide space-charge neutralization in the emitter-collector gap so that the high current densities may flow across the gap unattenuated. The function of the cesium reservoir is to provide a source of cesium atoms, and to provide a reserve in the event that cesium is lost from the plasma by any mechanism. This can be done with a liquid cesium metal reservoir in which case it is heated to the desired temperature with auxiliary heaters. In a TFE, however, it is desirable to have the reservoir passively heated by the nuclear fuel. In this case, the reservoir must operate at a temperature intermediate between the emitter and the collector, ruling out the use of liquid reservoirs. Integral reservoirs contained within the TFE will produce cesium vapor pressures in the desired range at typical electrode temperatures. The reservoir material that appears to be the best able to meet requirements is graphite. Cesium intercalates easily into graphite, and the cesium pressure is insensitive to loading for a given intercalation stage. The goals of the cesium reservoir test program were to verify the performance of Cs-graphite reservoirs in the temperature-pressure range of interest to TFE operation, and to test the operation of these reservoirs after exposure to a fast neutron fluence corresponding to seven year mission lifetime. In addition, other materials were evaluated for possible use in the integral reservoir

  20. Effects of Reservoirs Releases on Tailwater Ecology: A Literature Review.

    Science.gov (United States)

    1981-09-01

    intlix i n totil woters exhibi t.ing these types of flutua, ~is(Tror sky ain. iecr 7 P1cc ot e r 190. Plec ~ -trosre us ri 11 not found in tai Iwaters...Coldwater seis( plec ( ptez--ns anti trout.) may be elimi nated by temeratures exceodiif ig hi r t 3)1 aaice leve~ls. Ilevatett temperatu~res -ilso may allow